ornl
ORNL/TM-9258
OAK RIDGE
NATIONAL
LABORATORY
Predicting Soil and Water Acidification
Proceedings of a Workshop
Dale W. Johnson
Ingvar S. Nilsson
John O. Reuss
Hans Martin Seip
Robert S. Turner
OPERATED BY
MARTIN MARIETTA ENERGY SYSTEMS, INC.
FOR THE UNITED STATES
DEPARTMENT OF ENERGY
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EPA ERL-Corvallis Library
00003822
ORNL/TM-9258
430R85001
ENVIRONMENTAL SCIENCES DIVISION
PREDICTING SOIL AND WATER ACIDIFICATION
Proceedings of a Workshop
Dale W. Johnson
Editor
With contributions from
Ingvar S. Nilsson
John O. Reuss
Hans Martin Seip
Robert S. Turner
A Workshop held in Knoxville, Tennessee
March 26-29, 1984
Funded by
The National Acid Precipitation
Assessment Program by the
U.S. Environmental Protection Agency
Hosted by
Oak Ridge National Laboratory
Oak Ridge, Tennessee
LIBRARY
U* ENVIRONMENTAL PROTECTION AGENCY
OORVAUJ6 ENVIRONMENTAL RESEAHCMUffl
200 SW 39IH OTWET^
CCRVAl US OREGON 97339
Date Published - January 1985
OAK RIDGE NATIONAL LABORATORY
Oak Ridge, Tennessee 37831
operated by
MARTIN MARIETTA ENERGY SYSTEMS, Inc.
for the
U.S. DEPARTMENT OF ENERGY
under Contract No. DE-AC05-84OR21400
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CONTENTS
Page
WORKSHOP SUMMARY 1
INTRODUCTION 2
SOIL ACIDIFICATION 3
KEYNOTE ADDRESS: Modeling the Effect of Acid Deposition on Soil
and Water Acidification (John O. Reuss) 3
Capacity-Intensity Concepts 3
The CO2-HCO3~ System 4
Soil-Solution Equilibria 5
Conclusions 10
DISCUSSION 11
Is Organic Sulfur Accumulation Important? 11
Is Sulfate Adsorption Reversible? 12
Can We Forecast Nitrogen Saturation? 12
What Regulates Nitrification? 13
Can Acidification Due to Vegetation Uptake and Humus
Formation Be Quantified? 13
Are Natural Processes Self-Limiting? 14
Is Weathering Stimulated by Acidification? 14
How Does Aluminum Mobilization Affect Vegetation Uptake? 14
Are Limiting Cations Conserved Even in the Presence of
Acid Precipitation? 14
WATER ACIDIFICATION 15
KEYNOTE ADDRESS: How Are Waters Acidified? (Hans Martin Seip) 15
Introduction 15
Aquatic Buffer Systems 15
Conclusions Reached at the Sandefjord Meeting 15
Soil-Water Interactions in the Catchment 16
Hydrology 16
Direct Effects 17
Mobile Anion Concept 17
Weathering and Cation Exchange 18
Sulfur Oxidation 19
Prediction of Acidification 19
External and Internal Sources of Soil Acidification 22
Historic Trends in Lake Acidification and Relation to
Activities in the Catchment 23
iii
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IV
New Conclusions and Areas of Uncertainty 23
DISCUSSION 24
EXAMINATION OF BIRKENES AND GARDSJON DATA SETS 26
INTRODUCTION 26
ANALYSIS BY D. W. JOHNSON 26
ANALYSIS BY I. S. NILSSON 31
SOIL SENSITIVITY CRITERIA 34
ACKNOWLEDGMENTS 37
REFERENCES 38
LIST OF ATTENDEES 42
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WORKSHOP SUMMARY
JOHNSON, Dale W. (Editor). 1985. Predicting Soil and Water
Acidification. Proceedings of a Workshop. ORNL/TM-9258.
Oak Ridge National Laboratory, Oak Ridge, Tennessee. 56 pp.
A three-day workshop was held at the Hilton Hotel in Knoxville, Tennessee on March
27-29, 1984, preceded by a one-day tour of sites at or near ORNL. Funding for the work-
shop was provided by the National Acid Precipitation Assessment Program by the U.S.
Environmental Protection Agency. One of the goals of this workshop was to develop a con-
sensus among the participants as to sensitivity criteria for acid deposition effects on both
soils and surface waters. As the meeting evolved, the workshop participants spent most of
their time in a very productive discussion of important processes and hypotheses regarding
soil and water acidification, primarily from the theoretical standpoint, using empirical data
to illustrate specific points. Only in the afternoon of the last day were sensitivity criteria as
such discussed, but all of the preceding discussions clearly related to this issue as well. The
workshop discussions, including sensitivity criteria, are summarized in this document.
A major highlight of this workshop was a meeting of minds among aquatic and terres-
trial scientists as to important mechanisms for surface water acidification. This paved the
way for assessment activities, probably in association with modeling efforts such as those
of John Reuss, Nils Christophersen, and Jack Cosby. No such consensus or knowledge is
available for forest effects, however, because the important mechanisms of forest effects
are not known. A concensus was reached as to appropriate sensitivity criteria for soil acidi-
fication and aluminum mobilization, but there was no consensus as to whether these
processes in themselves are responsible for reported widespread forest dieback and decline.
Thus, assigning forest effects sensitivity criteria at this time would be premature at best
and very possibly misleading.
Two major areas of research were identified as most in need of further research: nitro-
gen (N) cycling (especially as affected by excess N inputs) and soil weathering. Nitrogen
is emerging as a key nutrient in terms of not only the beneficial, effects of nitrogen deposi-
tion to N-deficient forests, but also the possible detrimental effects of excess nitrogen depo-
sition on nutrient imbalances and on nitrification and associated soil acidification. Soil-
weathering rate remains one of the least understood of the master variables controlling soil
acidification, even after many years of recognition of its great importance.
A third in this series of workshops is being planned and will be hosted by Peter Dillon
in Ontario in 1985.
Dale W. Johnson
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INTRODUCTION
(Dale W. Johnson)
One of the concerns relative to acid deposition is its effect on soil and surface water
acidification. However, controversy surrounds this issue because of a gap in the under-
standing of the processes whereby acidification occurs. In view of this problem, Prof. Folke
Andersson of the Department of Ecology and Environmental Research, The Swedish
University of Agricultural Sciences, called an informal three-day workshop in Uppsala,
Sweden, in June 1982. The title of the workshop was "Simulation Models of Water Aci-
dification." The meeting was preceded by a two-day tour of research sites in southern
Sweden. Participation was by invitation only and was "restricted to scientists with experi-
ence in the field" in an effort to keep the group small and the discussions as meaningful
and as factually accurate as possible. Each participant was asked to solicit travel expenses
from his own sponsoring agency. At the conclusion of that workshop, it was agreed that
another meeting of the same type within a year or two would be productive. To that end,
an ad hoc organization was appointed by Prof. Andersson as follows:
Chairman Dale W. Johnson
Group Members and Areas of Responsibility
Water acidification Nils Christophersen
Hans Martin Seip
Groundwater acidification Gunnar Jacks
Soil acidification Dale W. Johnson
Ingvar S. Nilsson
Our objectives for the 1984 workshop were to (1) critically evaluate data sets from selected sites to
determine, insofar as possible, the degree to which soils and surface waters have been acidified by
acid deposition; (2) review and evaluate models of soil and surface water acidification; and (3)
arrive at a consensus as to appropriate sensitivity criteria for soil and surface water acidification.
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SOIL ACIDIFICATION
The first day of the workshop was devoted primarily to discussions on soil acidification and
related processes, although the subjects of soil-water interactions and water acidification were
touched upon. The session began with a keynote address by John Reuss (summarized in the follow-
ing section), followed by a group discussion of several key questions relating to soil acidification by
both natural and anthropogenic mechanisms.
KEYNOTE ADDRESS: Modeling the Effect of Acid Deposition on Soil and Water Acidification
(J. O. Reuss, Colorado State University, Fort Collins, Colorado)
The acidification of soils and waters due to acid deposition involves a number of complex
processes. As might be expected in a situation where the processes are not generally well understood
and the issue is of major economic importance, considerable controversy has resulted. Responsible
scientists differ substantially in their interpretation of the available information, and some have
questioned whether significant acidification of either soils or waters could take place as a result of
the levels of deposition currently encountered (e.g., Rosenqvist et al. 1980, Krug and Frink 1983).
In spite of the overall complexities, we found that a fairly simple model consisting of chemical
relationships that are reasonably well known and accepted can be very useful in understanding the
probable responses of soil and water systems to acid deposition. Because of the interactions among
the processes described by these relationships, it is essential that they be considered simultaneously
and not applied in a piecemeal manner.
Due to time limitations, the material that can be covered here is limited. After a brief discus-
sion of the capacity-intensity concepts, I will discuss the CO2-HCO3~ equilibrium and soil-solution
equilibria, as well as the effects of acid deposition on soil solution and surface water chemistry.
Capacity-Intensity Concepts
Much of the literature concerning the effect of acid deposition on soils and the soil-mediated
effects on surface waters has focused on the capacity of the soil to adsorb the proton input. Con-
sider, for example, a system receiving annually 1 m of pH 4.2 rainfall and an equal amount of acid-
ity as dry deposition, for a total of 0.125 eq H+/m2. If this input falls on 30 cm of soil with a cat-
ion exchange capacity (CEC) of 0.15 eq/kg, a bulk density of 1.2, and a 15% base saturation, a
comparison of the pool sizes scaled to the annual input of H+ would be about as follows:
Annual H+ input — 1
Exchangeable base — 65
Exchange acidity — 365
Obviously, it would require many decades (centuries in deeper soils) for this input to bring
about a significant change in total soil acidity. A significant change in the exchangeable base cation
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pool due to replacement by acid inputs might occur in a few decades, but this reduction would be
mitigated by the release of these cations by weathering processes. The reduction will be further
mitigated in some acid soils where the replacement efficiency of the input acidity for exchangeable
bases may be substantially less than 1.0.
From considerations such as these, many scientists concluded that soil effects due to acid depo-
sition or soil-mediated effects on surface water are likely to occur only on soils with very low CEC
and, therefore, on soils that are highly susceptible to changes in base saturation due to cation loss.
However, the capacity effects due to these changes in pool size are not the only manifestation of
acid deposition inputs. Changes in soil solution composition that may have a profound effect both
on terrestrial ecosystems and on surface and groundwater quality may occur without significant
changes in these pool sizes. It is on these so-called intensity factors that we will focus during the
remainder of the presentation.
The CO2-HCO3~ System
While the overall importance of the CO2-HCO3~ equilibrium in determining the properties of
both soil solutions and surface waters is well known, some of the implications, particularly the role
of CO2 partial pressure (pCO2) in determining the alkalinity of the drainage water, are often
neglected. In acid soils we can neglect the CO32~ ion so that the reaction can be written as
CO2 + H2O ^ H+ + HCO3~ . (1)
From this reaction we obtain the equilibrium expression,
(H+) (HC03-) = Kc • pC02 , (2)
where the material in parentheses refers to activities (or partial pressure in the case of pCO2). If
the concentrations are in microequivalents per liter (for our purposes, concentrations and activities
may be taken as equal) and the CO2 in percent, KC will be about 150. From Eq. (2) we find that at
0.03, 0.3, and 3% CO2 the product [(H+) (HCO3~)] is equal to 4.5, 45, arid 450, respectively. In
pure water a tenfold increase in CO2 results in both H+ and HCO3~ increasing by a factor of VTO
(i.e., 3.16) (Table 1). As a result, increasing CO2 from 0.03% (near atmospheric) to 0.3% decreases
pH from 5.67 to 5.17, while at 3% the pH will be 4.67. In pure water the H+ and HCO3~ concen-
trations are equal and the alkalinity, defined here as
alkalinity = (HCOD + (OFT) - (H+) , (3)
remains zero at all CO2 levels.
Acid soils are buffered by internal processes, and pH changes with varying CO2 partial pres-
sures are usually small. Because the product (H+) • (HCO3~) must increase with the CO2 partial
pressure (Eq. 3.) and (H+) is fixed by soil processes, the response to changing CO2 levels in the soil
is mostly in the HCO3~ concentration, and thus is reflected in the alkalinity of the soil solutions.
This is illustrated in Table 1 (lines 4-12). For example, at pH 5.67 and 0.03% CO2, the H+ and
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Table 1. The effect of pCO,on pH, H+, and HCO,~ In pure waters
and in soil solutions buffered by Internal soil processes
H+ HCOj- Alkalinity
Line CO, K(CO2), pH
Pure water
\
2
3
0.03
0.30
3.0
Soil solutions
4
5
6
7
8
9
10
11
12
0.03
0.30
3.0
0.03
0.30
3.0
0.03
0.30
3.0
4.5
45
450
(buffered)
4.5
45
450
4.5
45
450
4.5
45
450
5.67
5.17
4.67
5.67
5.67
5.67
5.17
5.17
5.17
4.67
4.67
4.67
2.1
6.7
21.2
2.1
2.1
2.1
6.7
6.7
6.7
21.2
21.2
21.2
2.1
6.7
21.2
2.1
21.2
212
0.67
6.7
67.2
0.21
2.1
21.2
0
0
0
0
19.1
210
-6.0
0
60.5
-21.0
-19.1
0
HCO3 concentrations are both 2.1 iteq/L, (the same as in water) and the alkalinity is zero. How-
ever, increasing CO2 to 0.3 and 3% increases the alkalinity of the soil solution to 19.1 and 210
/xeq/L, respectively. Increasing CO2 would have no effect on the alkalinity of water not buffered by
soil processes.
A soil solution at pH S.67 will have positive alkalinity if the CO: content, of the soil gases is
above 0.03%. At a solution pH of 5.17 the alkalinity will be positive above 0.3% CO2, and at pH
4.67 it will be positive above 3%. In this alkalinity-generating process, equal amounts of H+ and
HCO3~ are formed (Eq. 1), but the HCO3~ concentration increases while the H+ is held constant
by soil buffering. We may think of the H+ as being consumed in the dissolution of soil minerals,
bringing A13+ into solution. The Al3"1" then displaces cations such as Ca2+, Mg2+, and K+ from the
ion exchange complex. The net effect is the formation of bicarbonates of these cations (i.e., alkalin-
ity).
The changes in alkalinity brought about in the soil solution by variations in soil pCO2 can
drastically affect the pH of the drainage water. The relationship between alkalinity and pH in
water that is not in contact with soil processes, as derived from Eqs. (1) and (2), is shown in Fig. 1.
The pH 5.17 soil solution (lines 7-9, Table 1) at CO2 levels of 0.03, 0.3, and 3% has an alkalinity
of —6, 0, and 60.5 M^q/L, respectively. When this water equilibrates with atmospheric CO2
(0.03%), the pH will be 5.17 if the soil CO2 is 0.03%, 5.67 at 0.3% CO2, and 7.1 at 3% CO2. Thus,
at a soil solution pH of 5.17 the drainage water pH would vary by nearly 1.9 units simply by
varying soil CO2 over a range that may commonly be found in the soil.
Soil-Solution Equilibria
When an acid forest soil is subjected to acid deposition, the concentration of the strong acid
anion (SO42~, and in some cases NO3~) will increase. In most acid soils the natural concentrations
of these anions are very low; a typical value for SC>42~ might be 20 peq/L. The HCO3~ is also low
due to the nature of the CO2-HCO3~-H+ equilibria described above (e.g., at pH 4.67 and 3% CO2
the concentration of HCO3~ will be about 20 jteq/L). While organic anions can be an important
constituent of soil solutions and drainage waters, one of the characteristics of acid forest soils is low
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8
1
-100
-50
ORNL-OWG 84-1616
I
„. 0.3
•*
0.03%
— 3.0
I
I
I
50
100
150
ALKALINITY (^eqL")
Figure 1. The relationship between the pH and alkalinity of water at 0.03, 0.3, and 3% CO2.
anion concentration. When such soils are subjected to acid deposition the increase in SO42 concen-
tration can be very significant, typically in the range of 100 to 300 neq/L. (The time required for
this increase in SO42~ can vary markedly; high-sulfate-adsorbing soils may not come into SO42~
equilibrium for decades.) This increase in anion concentration can have a very important influence
on the cation composition. Not only will the total cation concentration in solution increase to main-
tain charge balance, but the relative amounts will also change. The most important of these changes
involves the H+, Ca2+, and A13+ ions (we will use Ca as a proxy for both Ca and Mg in this dis-
cussion). These responses can be described by the use of three relationships familiar to many of
you, which in the interest of time I will present without discussing their derivation or their limita-
tions. The first is the relationship between Al3"1" and H+:
- Ka(H+)3 ,
(4)
i.e., the activity of the A13+ ion is proportional to the third power of the H+ activity or, in negative
logarithm form,
3 pH - pAl
(5)
Values of KA in the soil may range from 7.0 or less to near 10. Useful reference points are the
values of 8.04 and 9.66 given by Lindsay (1979) for gibbsite and amorphous A1(OH)3, respectively.
A plot of this relationship for a representative set of KA values is shown in Fig. 2. The implications
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1000
800
600
ORNL-DWG 84-1612
0)
fO
< 400
200
I
25
50
75
L'1
100
125
Figure 2. The reUtkwshlp betweca A|3+ ud H+,
coefficients are assumed to be 0.96 for H and 0.70 for Al
3+
3 pH - pAl values In the ruse of 8.0 to 9.5. The activity
of the shape of these curves are twofold. First, if the value of KA is high the system is highly buf-
fered. For example, if KA is 9.5 the H+ concentration is unlikely to exceed about 30 j&q/L (pH
4.5), as any further H+ will only result in increased A13+ in solution. Second, as shown by the
upward curvature of the lines, increasing anion concentrations will result in increases in total
cations and in the proportion of A13+ relative to H+. This consequence can be stated as a general
principle, i.e., increasing solution concentration will increase the proportion of the cations with the
higher valence.
The second relationship is that between Ca2+ and A13+, which I describe below using the
equation of Gaines and Thomas (1953):
(A13+)2
(Ca2+)
2+\3
(6)
The parentheses denote activities in the solution phase, Kg is the ion exchange constant that reflects
the thermodynamic properties of the exchanger, and CaX and A1X are the fractions of the total
exchange sites occupied by the Ca+ and A13+ ions, respectively. Equation (6) states that the activ-
ity of A13+ in solution is proportional to the 3/2 power of the Ca2+ activity, i.e.,
= KB(Ca2+)3/2
(7)
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8
The proportionality constant KB is a function of the degree of saturation of Ca and Al and of the
constant Kb (Eq. 6.)- These relationships tell us that if the solution concentration increases due to
increased sulfate or nitrate from acid deposition, the Al3+:Ca2+ ratio in solution will increase so
that the activity of A13+ remains proportional to the 3/2 power of the Ca2+ activity (Fig. 2).
Again, an increase in solution concentration results in a shift toward the ion of higher valence. This
is an intensity response and occurs immediately as the concentration changes.
The lines in the plot of A13+ vs Ca2+ (Fig. 3) also curve upward, due to an increase in the
fraction of A13+ as the total concentration increases. For the Kg value used to construct Fig. 2, this
curvature increases markedly as the fraction of exchange sites occupied by Ca is reduced below
about 0.2. The effect of increasing values of Kg is similar to that of increasing Ca saturation. Thus,
increasing Kg has the effect of decreasing the Ca saturation at which the change in the Al3+:Ca2+
ratio in solution due to higher concentration becomes significant.
'ORNL-DWG 84-1615
KQ "0.5
500
600
Figure 3. The relationship between A13+ and Ca2+ In soil solution, with the fraction of the exchange sites occupied by
Ca2+ in the range of 0.05 to 0.20. Log of the Gaines-Thomas exchange coefficient is 0.05 and the activities of Ca and
AI3+ are 0.85 and 0.70, respectively.
While the effect of an increase in solution concentration due to acid deposition will be a higher
proportion of A13+ in solution relative to Ca2+ (actually relative to all mono- or divalent cations),
the total amount of all ions in solution will increase. Thus, the export of Ca2+ is accelerated, even
though the Al3+:Ca2+ ratio is reduced. If the exchangeable Ca pool is depleted due to increased Ca
loss over time, the Ca saturation will be reduced and the proportion of A13+ in solution will be fur-
ther increased.
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The third relationship is that between Ca2"1" and H+. Combining Eqs. (4) and (6) we obtain
the rather formidable-appearing Eq. (8),
(Ca2+)
K2/3
CaX
(8)
(A1X)2/3
This is more familiar to soil scientists in the form,
pH - 1/2 pCa
(9)
where KL is the well-known "lime potential." Equation (8) simply states that in the soil solution the
Ca2+ activity is proportional to the square of the H+ activity, and that the proportionality is deter-
mined by the A13+-H+ proportionality constant (Ka), the ion exchange constant (Kg), and the frac-
tion of exchange sites occupied by Ca and Al. Figure 4 shows the H+-Ca2+ relationship in soil
solutions of varying lime potential. The response of the system to increased solution concentrations
from acid deposition inputs is again to increase the proportion of Ca2"1" (i.e., the ion of higher
valence) (Fig. 4). This figure serves to illustrate the concept of ion exchange buffering. For exam-
ple, at a lime potential of 3.00, a soil solution pH of 4.3 could only be attained if the Ca concentra-
tion were about 1000 jieq/L. As Ca saturation is reduced the lime potential decreases, allowing pH
ORNL-DWG 84-1614
4000
0)
•f
CM
o
2000
1
325 3.00
275
25
50 75
H + ^eq LH
100
125
Figure 4. Hie relationship between Ca2+ and H+ in soU solution for lime potential values in the range of 2.25 to 3.25.
Calculations assume activity coefficients of 0.96 and 0.8S for H and Ca , respectively.
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10
to decrease. Eventually, the pH decrease will be buffered by bringing A13+ into solution (Fig. 2)
and the pH at which this A13+ buffering occurs will be determined by KA.
One of the problems with using Eq. (6) is that the ion exchange constant (Kg) is difficult to
measure. However, if the solubility of A13+ (Ka or KA), the degree of Ca and Al saturation, and
the lime potential are known, Kg can be calculated by rearranging Eq. (8). •
Conclusions
It is a relatively simple matter to combine the relationships in Eqs. (2), (4), and (6) with the
charge balance requirement to obtain a set of simultaneous equations such that if the various con-
stants and the Ca and Al saturation of the exchange complex are known, the composition of the
major cations in solution can be calculated for any combination of anion strength and pCO2. Addi-
tional ions can be included using similar relationships. Several current models are based on similar
concepts (Reuss 1980, Christophersen et al. 1982, Chen et al. 1983). Calculations of this type pro-
vide a quantification of the "salt effect" mechanism proposed by Seip (1980). The results indicate
that in some low base saturation soils the increase in the anion concentration in solution due to acid
deposition inputs may cause a significant increase in the A13+ concentration in the soil solution.
The increase in Al can, under certain conditions, have profound implications for both the plant
component of the ecosystem and the quality of the drainage water. The fact that A13+ is toxic.to
many plants is well known. Unfortunately, the levels at which various forest ecosystems will show
significant effects are not well established. The A13+ concentration of the drainage waters is also
critical. Within the pH range critical to many aquatic species, A13+ effectively acts as an acid.
Thus, the alkalinity of the water (Eq. 3) can be reduced by either H+ or A13+. Soil solutions with a
low but positive alkalinity may develop negative alkalinity, resulting in a substantial depression in
pH of the drainage water. This depression may occur as a direct result of the acid deposition input
without the necessity for a reduction in base cation status. In other cases, A13+ will not be signifi-
cantly increased unless base saturation is reduced by cation export. Soils with a large reservoir of
base cations, or those that release substantial cations as a result of mineral weathering processes,
may not develop increased A13+ concentrations, even under prolonged exposure to acid deposition.
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DISCUSSION
Dale Johnson presented a list of key processes relating to soil acidification as well as a series of
questions that were addressed during the day (Table 2). For the purposes of this report, the discus-
sions are summarized according to their relationship to the questions listed in Table 2.
Table 2. Key processes and questions relating to soil acidification
(presented for group discussion)
Questions
Inputs
Atmospheric sulfur
Atmospheric nitrogen
Naturally produced acids
Responses
Leaching
Weathering
Vegetation uptake and cycling
Is organic sulfur accumulation important?
Is sulfate adsorption reversible?
Can we forecast nitrogen saturation?
What regulates nitrification?
Can the acidification effects of vegetation
uptake and humus formation be quantified?
Are natural processes self-limiting?
Is weathering stimulated by acid input?
How does aluminum mobilization affect
vegetation uptake?
Are limiting cations conserved even with
acid deposition?
Is Organic Sulfur Accumulation Important?
Johnson initiated this discussion by stating that although sulfur is in the organic form in most
soils, SO42~ adsorption to Fe + Al oxides (or the lack of it) appears to be the dominant process of
SO42~ accumulation in areas receiving elevated atmospheric sulfur inputs. He supported this
hypothesis with two observations: First, forest ecosystems on Spodosols in the northeastern United
States generally do not show a net SO42~ retention (iie., SO42~ outputs > inputs), whereas forest
ecosystems on Ultisols in the southeastern United States generally do retain SO42~. This is consist-
ent with current information on the relative abilities of these two soil orders to adsorb sulfate
(Johnson and Todd 1983), although this does not imply that all Ultisols adsorb more SO42~ than
all Spodosols. He also noted that the picture is not at all clear for Inceptisols, where SO42~ adsorp-
tion properties appear to vary enormously.
Second, lysimeter studies in Ultisols indicate little SO42~ retention in organic-matter-rich sur-
face horizons but considerable retention in Fe + Al-oxides-rich subsoils (Johnson et al. 1981; Kelly,
11
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12
in press; Richter et al. 1983). He noted, however, that SO42~ mineralization from surface soils on
Walker Branch Watershed, Tennessee, was very large (Johnson et al. 1982) and thus organic sulfur
transformations must be important and cannot be neglected.
Johnson then asked Mark David, who has considerable experience in organic and inorganic sul-
fur transformations in Spodosols, for a rejoinder. David reviewed the sulfur studies he and his
colleagues have conducted (David et al. 1983, 1984) which show large rates of sulfur incorporation
and turnover into organic matter. He basically concurred, however, that net SO42~ retention in for-
est soils appeared to be governed by adsorption properties.
Is Sulfate Adsorption Reversible?
The reversibility of SO42~ adsorption and incorporation into organic matter was discussed
without definitive conclusions, except that variability would no doubt be large.
Egbert Matzner recounted studies at Soiling, West Germany, which indicate that the precipita-
tion of jurbanite (A1OHSO4) at first caused net SO42~ retention in soils at that site. Later, how-
ever, as soil solution pH declined and jurbanite became unstable, soils began showing a net SO42~
and A13+ release. Clearly, jurbanite formation is a very important consideration for soil SO42~
interactions that can lead to patterns quite different from SO42~ adsorption, that is, SO42~ desorp-
tion would not be expected to occur until solution SO42~ concentrations drop or solution pH
declines.
Can We Forecast Nitrogen Saturation?
Helga Van Miegroet and Jan Mulder were asked to briefly review studies of nitrogen fluxes in
red alder (Alnus rubra) stands in a relatively unpolluted area of Washington State, USA, and
coniferous and deciduous stands in The Netherlands. Red alder is a nitrogen-fixing species, and it
appears to have caused excess nitrogen accumulation and associated high rates of NO3~ leaching
after 40 years of site occupation. The net H+ generation from nitrification and nitrate leaching in
this stand is nearly 4 keq-ha~'-year~' (Van Miegroet and Cole, in press), a value quite compara-
ble to estimated anthropogenic H+ input at Soiling, West Germany (Ulrich 1980). Surface soils in
the red alder stand are O.S pH units lower than those in an adjacent Douglas-fir (Pseudotsuga men-
ziesii) stand, and according to calculations by John Reuss there is evidence of A13+ mobilization
during seasonal peaks in NO3~ concentration (up to 2000 ^eq/L). Nonetheless, Dale Cole pointed
out that the stand is quite healthy for its age and there is every reason to believe that natural suc-
cession to conifers [Douglas-fir, western hemlock (Tsuga heterophylla)] will proceed normally.
Jan Mulder then reviewed the work he and his colleagues conducted in forests of The Nether-
lands receiving high rates of nitrogen and sulfur inputs primarily as gaseous (NH3 and SO2) deposi-
tion to forest canopies. These gaseous inputs result in large inputs of (NH4)2SO4 to the forest floor
in throughfall (Van Breemen et al. 1983). The high rates of NH4+ stimulate nitrification in the
soil, and the net result is large exports of soil cations, with both SO42~ and NO3~ leaching. Coin-
cidentally, the magnitude of the leaching rates in these forests was similar to that in the natural red
alder stand.
Egbert Matzner reviewed the nitrogen situation at Soiling, where nitrification pushes
(presumed to be caused by favorable conditions for nitrification) during warm, dry summers cause
A13+ mobilization and damage to tree roots. By comparing different sites with varying degrees of
soil acidification, it was concluded that the high base saturation of the exchange sites reduces the
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13
risk of root damage following acidification pushes. Reduction of base saturation by SO42~ leaching
therefore leads to increasing root damage by acidification pushes.
None of these investigators could provide a framework for forecasting nitrogen saturation,
although each knew at least the approximate magnitude of nitrogen inputs at their N-saturated
sites (~80 kg-ha~'-year~' at the red alder site, 65 kg-ha"1-year"1 at The Netherland sites, and
40 kg-ha~'-year~' at the Soiling site). GOran Agren proposed a model for determining nitrogen
saturation based on his nitrogen productivity model (Agren 1983). The model relies on foliar nitro-
gen content (which varies with foliage biomass as well as N concentration) as a index of degree of
nitrogen saturation. Assuming 20% of incoming nitrogen is taken up by trees (based on fertilizer
studies), Agren can calculate the actual time needed to reach nitrogen saturation for a given site.
Immobilization of nitrogen in soil organic matter is not considered, however. Johnson questioned
whether 20% tree uptake would apply to atmospheric nitrogen inputs, which are spread fairly
evenly through time, as opposed to one-shot fertilizer nitrogen inputs.
What Regulates Nitrification?
This much-debated question was addressed by Vitousek et al. (1979) among others and a full
review of it was not possible here. Paul Bulgden had indications of nitrification inhibitors at his
sites in Belgium, whereas others (Johnson, Van Miegroet and Cole, Mulder) suspected NH4+ sup-
ply as the major factor. There is no doubt that inhibitors exist at some sites, whereas NH4+ supply
is important at other sites.
Once again the question of slow, steady atmospheric nitrogen inputs vs one-shot fertilizer appli-
cations was raised. Johnson discussed results of a fertilizer study where quarterly applications of 25
kg/ha of nitrogen as urea stimulated more nitrate leaching than annual 100-kg/ha applications.
Slow, steady inputs of NH4+ are probably optimal for building populations of nitrifying organisms
in soil, and thus nitrogen saturation (defined as a state where NO3~ export ^ N input) may be
more rapidly approached with atmospheric nitrogen inputs than equivalent inputs of nitrogen as
one-shot fertilizer applications.
Can Acidification Due to Vegetation Uptake and Humus Formation Be Quantified?
Several schemes have been proposed for quantifying the acidification effects of vegetation
uptake and humus formation (as well as natural leaching), all of which involve the same basic
assumptions (Ulrich 1980, Nilsson et al. 1982). There appeared to be general agreement as to the
methods to be used to estimate H+ production from natural leaching (by net anion production) and
humus formation (estimate organic matter accumulation and multiply by an average cation
exchange capacity for humus, usually near 2-3 keq/kg), but the methods used to estimate acidifica-
tion from plant uptake are less clear. This is due in part to uncertainties about the form in which
nitrogen is taken up, as NH4+ (acidifying) or as NO3~ (alkalizing). For the other major elements,
the form of uptake is known (Ca2+, K+, Mg2+, SO42~~). It was agreed that if nitrogen is mineral-
ized from organic matter and subsequently taken up by plants, the net acidifying effect is zero.
Thus, only external inputs of NH4+ and NO3~ need be considered in regard to acidification. Simi-
larly, organic cation mineralization followed by uptake would have no net effect on acidification
(Van Breeman et al. 1983). However, the proportions of cation uptake from organic vs inorganic
soil sources are seldom known.
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14
Are Natural Processes Self-Limiting?
This question has been raised several times prior to the workshop by John Reuss. He pointed
out that natural leaching agents are fundamentally different from atmospheric inputs in that the
former are weak acids (carbonic and organic) and therefore will tend to "turn themselves off as
soils acidify. This point brought little debate, but it was not clear how acid these natural leaching
agents (especially organic acids) could make soils and soil solutions before turning themselves off.
Is Weathering Stimulated by Acidification?
This question was centered on the possible compensation for accelerated acid input by an accel-
erated rate of exchangeable cation replacement by weathering. Egbert Matzner noted that
estimated rates of weathering for the Soiling site were close to estimates of weathering of soils over
geologic time periods (since deglaciation) in the same region, suggesting that weathering had not
accelerated to compensate for acid deposition. Arne Stuanes was asked to review his results from
the Norwegian acid irrigation studies in this context. He reported that weathering (as determined
by the mass balance approach, where inputs and outputs are compared to the actual changes in soil
exchangeable cations) had been accelerated by accelerated cation leaching, but the compensation
was not total because decreases in exchangeable base cations did occur with acid treatments. Helga
Van Miegroet reported that the weathering rates in the red alder stand must have been accelerated
considerably as compared to those in the Douglas-fir stand because, for example, the exchangeable
Mg2+ supplies in the red alder soil equalled only a 3-year supply at current leaching rates.
It seemed to be the group's conclusion that weathering could indeed be stimulated by increased
acid input, but that the rates of weathering will be quite variable and are usually not known. It was
clear that determining weathering rates and the development of additional techniques for the deter-
mination of weathering rates constitute pressing research needs.
How Does Aluminum Mobilization Affect Vegetation Uptake?
The question of A13+ damage to tree roots and other hypotheses regarding causes of tree die-
back and forest decline were not discussed during this workshop. When asked about this, Egbert
Matzner replied that the subject was so involved and complex that it would have to be (and will be)
addressed in another workshop devoted entirely to it. The group agreed and thus this issue was not
considered per se, but only indirectly in the context of soil acidification.
Are Limiting Cations Conserved Even in the Presence of Acid Precipitation?
Johnson noted that trees take up cations individually for individual reasons and that we cannot
use the sum of base cations as a particularly useful index of site nutrient cation status. Even when
acid deposition is causing net export of base cations, not all base cations are necessarily being lost
(i.e., Ca shows a balanced budget, while K, Na, and K show a net export from the Fullerton site on
Walker Branch). It would seem that, from both a chemical and biological perspective, limiting
cations are likely to show a smaller net loss from a system than nonlimiting cations. However, an
argument can be made that even small additional losses of limiting cations are more detrimental
than greater losses of nonlimiting cations. This, as well as the entire area of acid deposition effects
on the cycling of individual cations, needs further investigation.
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WATER ACIDIFICATION
KEYNOTE ADDRESS: How Are Waters Acidified? (Hans Martin Seip. Central Institute for
Industrial Research, Oslo, Norway)
Introduction
Though I was asked to discuss aquatic acidification, most of my talk will be on soil-water
interactions. The most interesting processes related to water acidification go on in the catchment. I
will therefore come back to many of the same processes that we discussed yesterday but from a
slightly different point of view.
To what extent has freshwater acidification occurred? We all know about the difficulties in
comparing recent and old measurements of pH and alkalinity. Perhaps the biological changes pro-
vide the most convincing evidence for acidification (e.g., see Overrein et al. 1980, Swedish Ministry
of Agriculture 1982).
Most likely many of the lakes in southernmost Norway have always had a very low alkalinity.
In such cases, pH shifts of 0.5 to 1 unit will have dramatic biological consequences. Studies of dia-
toms in sediments have also been used to estimate pH changes in lakes. I will return to this later.
Aquatic Buffer Systems
Acidification is by definition a change in the H+ concentration, but it is often convenient to
talk about change in alkalinity or acid neutralizing capacity (ANC). One possible definition of
ANC in a system with aluminium and organic acid is
[ANC] = [HCO3~] + 2[CO32~] +
[A1(OH)2+] + 2[A1(OH)2+] + 4[A1(OH)4-]
+ [RCOO-] + [OH~] - [H+]
[ANC] = Jf_n ft d(PH) ,
where /9 is the buffer intensity.
Organic acids will usually buffer over a broad pH range, with maximum between 4 and 5. In
the example, the bicarbonate system starts to dominate at pH slightly less than 6 (equilibrium with
atmospheric CO2 is assumed). Aluminum dominates at low pH values. The buffering caused by the
sediments may also be of considerable importance.
Conclusions Reached at the Sandefjord Meeting
I will discuss the causes of acidification by going back to the Sandefjord meeting held 4 years
ago. My discussion there concerned three conceptual models of water acidification (Seip 1980): (1)
15
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16
the model that is based on a direct effect (i.e., assuming that a substantial fraction of the precipita-
tion reaches rivers and lakes essentially unchanged); (2) the model that emphasizes the increased
deposition of mobile anions (in particular SO42~); and (3) the model that is based on effects on
freshwater through a change in soil acidity brought about by acid precipitation and other causes
(e.g., changed vegetation).
The conclusions I reached at the Sandefjord meeting, mainly based on Norwegian studies,
were:
(1) The fraction of the precipitation reaching rivers and lakes essentially unchanged is normally
small. Thus the direct effects are small, but not negligible.
(2) Changes in the soil may occur as a result of acid precipitation. This may contribute to freshwa-
ter acidification. However, in my opinion, these effects are also likely to be small, but not negli-
gible.
(3) Though there seems to be no consistent pattern of changes in land use that may explain
regional acidifications, these factors are probably contributing in some areas.
(4) The easiest way to understand the acidification of freshwater is by considering the increased
sulfate deposition. The increased concentrations of mobile anions explain at least a substantial
part of the observed acidification.
I'll leave this subject with the question, "To what extent has recent research strengthened or
weakened these conclusions?"
Soil-Water Interactions in the Catchment
A catchment is a very complex system, and a large number of factors/processes may possibly
play a role in connection with acidification:
— Hydrology
— Deposition of mobile anions
— Canopy interactions
— Carbonate system (pCO2)
— Organic and other weak acids
— Cation exchange
— Adsorption of anions in soil
— Acid hydrolysis of minerals
— Oxidation and reduction reactions (S and N compounds)
— Uptake and release of ions by vegetation.
Hydrology
It is evident that soil-water interactions depend critically on the hydrology. A satisfactory
knowledge of the hydrology is therefore extremely important in understanding acidification. Four
years ago we did some work on the Birkenes model. The hydrologic model consists simply of two
reservoirs, one representing the upper soil horizons and the other the mineral soils (Christophersen
et al. 1982). Even at that time we were aware that this model was too simple. Studies of natural
isotope ratios (in particular, 18O/16O) may be used to estimate the amount of "old water" from the
catchment in the runoff. Studies by Rodhe (1981) show that even during snowmelt the fraction of
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17
melt water generally is fairly small. Our first I8O studies at Birkenes indicated that at high flow the
model gives too much water from the upper reservoir to the stream. In cooperation with Peter Dil-
lon and his group we recently tried to modify the Birkenes model for an inflow stream to Harp
Lake (Harp 4). We then introduced "piston flow" [e.g., water coming from the upper reservoir may
push out an equivalent amount from the B-reservoir (Seip et al. 1984)]. Other possible improve-
ments are to use a model based on the variable source area concept to introduce channel flow.
In many catchments (e.g., Birkenes), the most critical pH values are observed at high dis-
charge such as during snowmelt. With our simple Birkenes model (also after introducing piston
flow), the reason is partly that the runoff contains a large fraction of water from the upper reser-
voir.
At the meeting in Bolton Landing (Acidification: Natural or Anthropogenic?) this past fall, Al
Lefohn presented snowmelt results from several areas. He argued that acid episodes are a natural
phenomenon. This is most likely true, but addition of sulfur anions, and sometimes NO3~, will
cause the episodes to be more critical and perhaps more frequent.
Direct Effects
Having discussed the hydrology it seems convenient to comment on what I call direct effects. I
still think my conclusion from Sandefjord is valid for most areas, but I realize that in some places
the lake water composition may come close to that of the precipitation. In particular, this is true for
some seepage lakes (i.e., lakes without surface inlets or outlets) such as those in Wisconsin
described by Jerry Schnoor and J. M. Eilers. Also, other lakes that occupy a large fraction of the
catchment, say 30 to 40% or more, will of course be considerably influenced by direct deposition
[e.g., Lake GardsjOn in southern Sweden (Nilsson 1984a)]. In most cases, however, the contact
between water and soil will be sufficient to cause a great modification of water chemistry. In the
SNSF project, we did some experiments with radioactive tracers to study this interaction (Overrein
et al. 1980). The I8O studies I mentioned seem to strengthen the conclusion about considerable
soil-water interaction even during snowmelt.
Data on streamwater chemistry during snowmelt from the Muskoka-Halibourton area in
Ontario point in the same direction. The variation in sulfate concentration during snowmelt is sur-
prisingly small. Because it is well known that most of the ionic impurities leave the snowpack with
the first meltwater, much of the sulfate must come from the soil. (Of course, the contact in the
beginning of the snowmelt could be small, but model calculations indicate that this is not the case.)
Mobile Anion Concept
Mobile anions are important as vehicles for cation transport through a catchment. In the origi-
nal Birkenes model we ignored all anions except SO42~. The stream is so acid that bicarbonate is
usually negligible. (We have now included bicarbonate in a version of the model that we apply to
Harp 4, see section on Prediction of Acidification). The argument for ignoring Cl~ was that it is
roughly compensated by Na+, both in precipitation and runoff. This approximation has been criti-
cized, and it is true that precipitation episodes with particularly high concentrations of sea-salts
may give acid surges in the runoff. This has been observed on the west coast of Norway (SNSF-
project), and I believe it has also been found in southwestern Sweden (neighborhood of Lake
Gardsjdn). A recent study in Scotland (Galloway area) seems to show the same effect.
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18
Nitrate is normally low in Norwegian freshwaters. The snowmelt period may be an exception,
as in the Storgama catchment in southernmost Norway where sulfate is the dominant anion, but
nitrate cannot always be neglected. We usually find high concentrations of sulfate and nitrate
simultaneously. This is different from the situation found for Woods and Panther lakes (Adirondack
Mountains) as shown by Galloway et al. (1980).
For Dart Lake (Adirondack Mountains), Driscoll and Schafran found no statistically signifi-
cant correlation between H+ + Al and sulfate, even though sulfate is the dominant anion. The H+
+ Al was, however, strongly correlated with nitrate. I do not know if the correlation reflects a
causal relationship; Ingvar Nilsson recently observed similar trends in the soil solution of lysimeters
(Nilsson 1984b). He suggested a mechanism involving basic aluminum sulfate [A14(OH)10SO4] that
may explain the results. Because the NO, emissions seem to increase quite rapidly, there is no
doubt that nitrate represents a potential problem.
Organic anions may also deserve a more detailed discussion than I gave at the Sandefjord
meeting. Krug and Frink (1983) recently criticized the "mobile anion" concept. They stated that an
increase in input of H2SO4 would lead to a decrease in organic anions and therefore not to an
increase in the sum of anions. Actually, the logic in their paper is not very clear. They argue that
acid input has little effect on pH of the soil and water, but the concentration of organic anions will
only decrease if the percolate becomes more acid. Furthermore, there is no experimental evidence
that a possible decrease in organic anions should be equivalent to the sulfate increase. Work by Dil-
lon, LaZerte, and others in the Muskoka-Halibourton area shows that the concentration of organic
anions is usually low during snowmelt, which is the period with the lowest pH values.
Weathering and Cation Exchange
We probably all agree that weathering and cation exchange are key processes in estimating
effects of acid deposition. We may also consider acid hydrolysis and oxidation processes. Hydro-
lysis of minerals and cation exchange are often treated together because these processes usually
result in consumption of H+ and production of Ca + Mg. It is useful, however, to make a distinc-
tion because the hydrolysis of minerals always consumes H+ (with the exception of quartz) and
cation exchange may actually acidify the percolate. Furthermore cation exchange is probably a
much faster process than hydrolysis.
Some recent estimates of H+ consumption (in meq/m2) during the weathering process are
given below
Van Breemen World average 310
etal. (1984) Range for 20 catchment 0-1590
Catchments with low acidification rate 40-350
Schnoor et al. Seepage lakes 23
Drainage lakes 80
The rate constant for hydrolysis of minerals is expected to vary with acidity, e.g.,
r = k[H+]a ,
where k and a are constants. Estimates of a are, however, very uncertain.
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19
Sulfur Oxidation
Even if we agree that sulfate is the most important anion in connection with acidification, it
does not necessarily mean that its source is anthropogenic. Mineralization of organic sulfur or oxi-
dation of other sulfur compounds (e.g., FeS2) is often important. This process had to be introduced
in the Birkenes model at an early stage. Also this sulfur may, of course, have atmospheric deposi-
tion as its origin. In the SNSF project, we did some experiments with radioactive sulfur showing
that sulfate supplied to a mini-catchment will take part in a number of complicated processes
(Overrein et al. 1980). Work by Mitchell, David, and others on soil from the Adirondack Moun-
tains confirms the importance of sulfate formation through organic sulfur mineralization.
Prediction of Acidification
Two recent attempts to predict changes in H+ (or in H+ 4- Al ions) are based on the mobile
anion concept.
Henriksen and Wright developed an empirical model (Henriksen 1982, Wright and Henriksen
1983). They consider a simplified system; for example, organic acid is neglected. Strong acid (SA)
may be expressed as
SA = H+ + 2Aln+ ~ HCO3~ .
For a change in nonmarine sulfate concentration in the water, a charge balance gives
ASA = ASO4* - A(Ca* + Mg*) .
A factor, F, is then defined
F = A(Ca* + Mg*)/ASO4*
ASA - (1 - F) AS04* .
For southernmost Norway, they find that F < 0.4 and suggest that the most likely value is F =
0.2.
Here F is the ratio of increase in nonmarine Ca + Mg to the increase in ASO4. An upper
limit for F was obtained by assuming that the Ca + Mg concentration in lakes in southernmost
Norway was negligible in industrial times. Wright and Henriksen (1983) give an estimate for water
quality in the "old days" that seems quite reasonable. They also estimated that a 30% reduction in
sulfate deposition would restore chemical conditions such that 22% of the lakes now experiencing
fishery problems should be able to support fish. If, however, a soil acidification due to factors other
than acid deposition occurred in this region, the formulas cannot be used without modifications for
predicting changes in water quality due to changes in deposition.
Christophersen et al. (1984) tried to make a prediction model based on the Birkenes model.
While modifying the model for the Storgama catchment, we noticed that fairly satisfactory agree-
ment could be obtained for most of the year by using only data for the upper reservoir.
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20
To use the model for low SO4 loadings we had to include bicarbonate. We then had four equa-
tions as given below. Actually this is the model presented by Reuss yesterday, just formulated dif-
ferently.
2[M2+] + 3[A13+] - 2[S042-] + [NCV] + [HCOj"]
KG
[M3+] [H+r3 = "KH,
[H+] [HC03-] = K PC02 ,
where M2+ is the sum of Ca2+ and Mg2+. All of the theoretical curves in Fig. 5 were calculated
with "Its,, = 10* •'. Curve (I) was obtained with pCO2 = 0 and KQ = 10~221; curve (II) with a
pCO2 in soil equal to 100 times that in the atmosphere, a pCO2 in water equal to two times that in
the atmosphere, and KG = 10~2-15; and curve (HI) corresponds to the same CO2 pressures, but K0
= io-2-37.
In Fig. 5 we compare simulated values of M2+ [= Ca2+ + Mg2+], A13+, and H+ with obser-
vations. Horizontal bars represent the median of observations; 75th and 25th percentiles are also
given. The model seems to show that, at least for this catchment, the mobile anion concept is use-
ful. If we want to use the model for prediction at very low values of [804] + [NOs], organic
anions may become important.
The model predicts that the main changes are in A13+ (a constant level of organically complexed Al
is added) and M2+, with fairly small changes in [H+] (F-factor = 0.45-0.65) except when [SO42~]
+ [NO3~] becomes very small. This is not in good agreement with the Henriksen- Wright model. It
is, however, important to remember that the Birkenes model was developed to describe day-to-day
or seasonal variations. If soil acidification does occur, our model may also give an F-factor equal to
0.2. Comparison thus seems to indicate some degree of soil acidification. Peter Chester reached a
similar conclusion on the basis of the lake data from southernmost Norway.
Often soil chemists point out that the amount of acid in the precipitation is low compared to
that amount needed to change the pH or base saturation in the soil. We must, however, remember
that the water does not flow homogeneously through the soil, but mainly follows channels or larger
pores. This does not mean that there is no soil-water interaction, but the amount of soil in contact
with the main flow of water may be just a small fraction of the total amount. A counter-argument
may be, however, that studies of 18O/16O ratios generally indicate long residence times and, thus,
perhaps better distribution of the water in the soil.
Experiments and field studies going on at present may contribute greatly to solutions of the
questions mentioned. I refer partly to data from the Canadian-Norwegian-Swedish RAIN project
and partly to the very interesting changes that seem to take place in lakes around Sudbury,
Ontario. The emissions from INCO at Sudbury have now been reduced to less than 50% of the
values in the mid-1970s.
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21
i i _T_._ in
50
100 150 200
[so2-]«[NOS] ,i
A At as Al3',
50
50
A M2*,
150
100
50
100 150 200
[SO^fNO^peql-1
50
100
150
200
Fig. 5. Medians of obscncd [H+k IAI3+l ud [M2+] with the 75th and 25th percentiles as tmetiaas of [SO42 ) +
[NO3 ). All available data for the Storgama catchment (n = 424) from 1974 to 1982 are included with three theoretical
curves (see text). Only total Al concentrations have been measured. We have therefore added 10 iicq/L to the computed
values to take organic complexes into account.
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22
Before leaving the subject of prediction, I should like to mention some very recent model
results by Rustad, Christophersen, and Seip. We carried out calculations for Harp 4 including those
for the anions SO42~ and HCO3~ and the cations M2+ [= (Mg2+ + Ca2+)], H+, and A13+. The
hydrologic model was mentioned previously. The pCO2 in soil was assumed to be a function of soil
temperature only. In Fig. 6, I plotted results for H+ during a snowmelt period. (The peaks are
somewhat higher than the observed values.) Then we tried a calculation with reduced sulfur deposi-
tion and reduced S-reservoirs, such that the SO4 concentration in runoff was reduced by roughly
50%. The pH change is nearly one unit. This is in agreement with some preliminary calculations by
Seip and Rustad (1984) showing that, in the pH range we are discussing here, quite large shifts
may occur for moderate changes in deposition.
Simulation results Harp
Snowmelt 1979
r1)
15
10
March
April
Fig. 6. Simulated daily H+ concentrations for Harp 4 daring snowmeh. Open circles correspond to present 804 con-
centrations in runoff. Filled circles were obtained for approximately a 50% reduction in the sulfate concentrations.
External and Internal Sources of Soil Acidification
I mentioned earlier experiments showing that acid precipitation may result in soil acidification.
There are also observations (e.g., from Sweden and Germany) showing that the soil has become
more acid during recent decades. Nilsson (1983) discussed increases in soil acidity in Swedish forest
soils and concluded that "To date no unequivocal evidence exists that points to a soil acidification
mainly caused by atmospheric deposition. The tree species replacement and ion accumulation in
plant biomass and humus seem to be the most important causes." In my view, atmospheric deposi-
tion has caused soil acidification in some areas in Germany.
In humid, temperate climate, soil acidification is a natural process, but usually at a slow rate.
Various anthropogenic activities may accelerate the process. If pine trees are planted on an area
previously covered by grass, the soil will certainly become more acid. Nilsson et al. (1982)
estimated net rates of acidification as the result of excess cation accumulation in trees and humus.
Table 3 is taken from a recent study carried out for EEC. The work by Nilsson et al. is probably
the basis for some of the numbers. These numbers seem fairly reasonable to me. I think, however,
the table may be a topic for further discussion.
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23
Table 3. Sources of acid Input to soil
(EuTironmental Resources Limited 1983).
Values in percent
Forest
Fertiliser/nitrification
Biomass growth
Tree harvesting
Humus decomposition/
organic acid production
Soil respiration
Acid precipitation
Agricultural
land
65-80
10-20
5-20
Peat
bog
70-90
10-30
Spruce
med. soil
20-40
10-15
20-40
25-50
Pine
poor soil
5-10
0-10
10-15
0-5
60-80
Historic Trends in Lake Acidification and Relation to Activities in the Catchment
Historic trends in acidification of lakes may be obtained by studying the diatoms in the sedi-
ments. There are some difficulties, however (e.g., what is the importance of bioturbation).
Nevertheless, it may be of interest to look at some results from various parts of the world.
In Lake Gardsjb'n, a slow acidification was found during the centuries up to a few decades ago
(Renberg and Hellberg 1982). There must certainly have been vegetation changes, etc., during this
period, but the pH decrease seems to be quite smooth almost all of the time. (There is, of course, a
long period between the layers used to determine pH.) Charles (1984) studied a sediment core from
Big Moose Lake in the Adirondack Mountains. From about 1800 until about 1950 the inferred pH
of the lake was —5.7. After 1950 the value dropped steadily to about 4.7. It is known that there
were major logging operations around Big Moose Lake in the last century, but lake pH does not
seem to have been affected. Also, the inferred pH for Round Lock of Glenhead, Galloway, shows
small variations for centuries; acidification seems to have started around 1850. Flower and Battar-
bee (1983) compared the acidification in Round Loch of Glenhead (no afforestation) to that in
Lock Grannoch (=70% afforestation). The acidification is similar in these lakes, though the details
in the diatom patterns are somewhat different.
New Conclusions and Areas of Uncertainty
Going back now to the conclusions I made 4 years ago (section 3, Conclusions Reached at the
Sandefjord Meeting), I do not think the modifications need to be too large. I did perhaps at that
time underestimate the importance of changes in soil properties, such as base saturation due to acid
deposition. As mentioned, the soil changes along macropores may be greater than those for the soil
on the average. Also one should perhaps pay more attention to nitrate than I did, though I still
think the first goal should be to reduce sulfur emissions. In Sandefjord I mainly discussed quite
acid systems, but also in these cases bicarbonate should be included, especially to be able to make
predictions for low levels of sulfate deposition.
Very briefly I would say that the main effort now should be directed toward obtaining better
prediction models for responses to changed emissions of SO2 and NO,. This will, however, include a
number of tasks, for example, obtaining better: (1) estimates of various sources of soil acidification,
(2) understanding of the hydrology, (3) estimates of weathering rates and their pH dependency, (4)
understanding of the importance of nitrate vs sulfate, (5) measurements of pCO2 in soils, including
seasonal variations, and (6) understanding of the aluminium chemistry in soil and water.
-------
DISCUSSION (Summarized by D. W. Johnson)
Following the keynote address by Seip, there were brief presentations by Bob Goldstein, David
Lam, Jack Cosby, Dick Wright, Michael Hauhs, Peter Dillon, and Richard Skeffington, which are
summarized below along with the discussions.
Bob Goldstein reviewed the Intergrated Lake-Watershed Acidification Study (ILWAS) model
(Chen et al. 1983, Chen et al. 1984) and the results of recent applications of the model to the
ILWAS watersheds to examine the role of hydrology, cation exchange, weathering, and climatic
variables in the acidification of lakes (Goldstein et al. 1984). He emphasized that the relative rout-
ing of water through different flow paths within a watershed is a major determinant of lake alkalin-
ity and lake vulnerability from acidification by atmospheric deposition. This is supported by results
from the Regional Integrated Lake-Watershed Acidification Study (RILWAS) as well as ILWAS.
The reader is referred to the above-cited publications for details.
David Lam presented surface water and groundwater model results which appeared to explain
the observed spatial gradient of the stream alkalinity in the Turkey Lakes watershed near Sault Ste
Marie, Ontario.
Jack Cosby reviewed data and modeling results for the White Oak Run watershed in Virginia,
where distinct seasonal peaks in alkalinity and base cation concentrations occur. The peaks were
thought to be the result of seasonal variations in soil pCO2, and some back-calculations were made
to estimate what soil CO2 pressures must have been. Johnson suggested that soil pCO2 itself can be
modeled, given CO2 evolution rates, soil porosity, and soil water content (e.g., see DeJong and
Schappert 1972). He also suggested that rapid, event collection of lysimeter water could be used to
back-calculate soil pCO2, because the kinetics of CO2 loss from waters in collection vessels was
apparently favorable. Calculations of kinetics need checking, however.
Michael Hauhs presented hydrology, soil solution, and stream chemistry results from a new
study at Lange Bramke in West Germany which may relate to both water acidification and forest
decline. He noted increasing NO3~ and A13+ concentrations on the north slope and decreasing
Ca2+ and Mg2+ concentrations in soil solutions on the south slope of the watershed. Symptoms of
forest dieback were also noted on the southern slope of the watershed, and the dieback was associ-
ated with Mg2+ deficiency. He hypothesized that base cation depletion occurred due to SO42~
leaching on the south slope and that A13+ mobilization by nitrate is causing root damage on the
north slope.
Dick Wright reviewed the Henriksen model and the modifications and applications of it to
North American surface waters (Wright et al. 1983). The reader is referred to that document for
details which will not be repeated here. Johnson questioned the very low values for the F-factor
used, the F-factor being the change in base cation concentration per unit change in sulfate concen-
tration. Wright reported an average value of 0.4, which would imply either extremely acid soils or
surface runoff with little contact with soil exchange sites. Reuss also questioned the low value,
pointing out that the value must be representative of only the most sensitive systems which have
already become acid and that the same factor is probably not applicable to those less sensitive sys-
tems which have not yet become acid.
24
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25
Peter Dillon reviewed results of surface water chemistry in the Sudbury area, where sulfur
emissions were reduced by 80% from the early 1970s to the early 1980s. Recovery of surface water
pH and alkalinity was very rapid and was associated with decreases in sulfate concentration. A sur-
face water pH rise of 1 unit within 5 years was not uncommon. The results are consistent with
those of soil SO42~ adsorption studies which show that Spodosols (Podzols) have relatively low
adsorption capacities. However, sulfate adsorption studies have not been conducted on soils of the
area and it is not known whether this or some other factor (e.g., hydrology) is the major reason for
the rapid recovery. Dillon also noted that the F-factor, or the change in base cation concentration
per unit change in sulfate concentration, was approximately 0.75 for this area, considerably higher
than the 0.4 value given as an average for sensitive regions by Wright et al. (1982). Dillon also
noted that weathering must have been significant even in these granitic soils, because calculations
indicated that it would have taken only 8 to 10 years to deplete the entire soil exchangeable cation
reserve.
Richard Skeffington reviewed studies in the United Kingdom where afforestation of pasture
land has caused increases in concentrations of major ions, including A13+, and resulted in the death
of trout. At Loch Grannoch (southwest Scotland), diatom records indicated that there was a sharp
decline in lake pH after sheep were removed from the pasture (Flower and Battarbee 1983).
Hypotheses for the changes include increased deposition (especially cloud moisture) onto the forest
canopies, decreased water flux (increased evapotranspiration) causing increased concentrations in
waters, sulfur mineralization due to plowing prior to afforestation, and increased organic acid
export due to plowing (Binns 1984).
-------
EXAMINATION OF BIRKENES AND GARDSJON DATA SETS
INTRODUCTION
The first item on the agenda was an examination of data sets from Birkenes watershed in Nor-
way and Gardsjo*n watershed in Sweden by Dale Johnson and Ingvar Nilsson. The idea for this ses-
sion was to try to resolve differences of opinion as to causes of surface water acidification by focus-
ing on a common data set and discussing important processes in the context of this data set.
Synopses of the individual presentations are given below.
ANALYSIS BY DALE W. JOHNSON
My approach to this analysis was to use selectivity coefficients of the Gaines and Thomas
(1953) type to calculate changes in surface water chemistry with arbitrary changes in SO42~ con-
tent. The basic equations for A13+ — M2+ or M+ exchange are:
(Al3+)2[m2+l3 = ,+ _ (Al3+)[m2+]3/2 -(1)
(M2+)3[A13+]2 W" l J (m2+)3/2Q,'/2 '
K2 =
(4)
where () denotes exchange phase, in equivalent fractions,
[] denotes solution phase (in /teq/L),
Q = selectivity coefficient,
K = exchange coefficient assuming no change in base saturation.
Given these equations along with the charge balance equation, one can take stream chemistry data,
assume the solutions to have been in equilibrium with a soil of unknown properties, and then calcu-
late K values. This is done below using the current concentrations in Birkenes streamwater (Table
4; Christophersen et al. 1982).
26
-------
27
Table 4. Blrkenes streamwater concentrations: Actual and calculated
Predicted concentration if SO4 = 30 fieq/L
No % BSa change 2X % BSa change
Ion
H+
pH
A13+
Na+
K+
CaI+
MgJ+
NH4+
2 cations'
SO42~
HCO3~
Cl
NO3
2 Anions
isiirrcm
cone.
33
4.48
71
123
7
67 (107)
40
<5
341
181
0
123
7
282
Na+ changes
25
4.60
32
94
5
63
219
30
0
123
7
160
Na+ constant
22
4.66 .
21
123
5
48
219
30
0
123
7
160
Na+ changes
20
4.70
20
75
4
99
218
30
0
123
7
160
Na+ constant
27
4.78
11
123
4
66
221
30
0
123
7
160
Base saturation.
The K values for the Birkenes watershed (from Table 4) are as follows:
= 2.62 X 10" <5>
lCn2+ + Mo2+l3 fK + l3 f*\
Ik§ ±_Mg—L = 547 _L*_J_ = 40 . (6)
243 l"- J =48
[A13+]2 [A13+]
We can then express total cations as a function of A13+:
Total cations = 341 = H+ + A13+ + Na+ + Ca2+ + Mg2+ + K+
= (506 [A13+])'/3 + A13+ + (2.62 X 104[A13+])'/3
+ (243 [A13+]2)'/3 + (4.8 [A13+])'/3
= 39.4 [A13+]'/3 + 6.24 [A13+]2/3 + A13+ .
At this point, A13+ can be solved for iteratively to match any total cation value. For our pur-
poses, I assumed a SO42~ reduction from 181 to 30 jteq/L (decrease of 151 neq/L) and a
corresponding decline in total cations (341 to 219 /ieq/L, ignoring the charge balance problems if
Al is considered to be A13+ in this water. If Al is A13+ or any charge greater than zero, an anion
deficit exists, implying the presence of organic acids which may control pH. I will not pursue this
controversial matter further in this exercise, however). The results of this calculation are given in
the third column of Table 4. Once an appropriate A13+ value is obtained to match total cations, all
other cations are solved for. The results show a very small change in pH, a 55% reduction in A13+,
a 41% reduction in Ca2+ + Mg2+ (which are bulked as m2+ in this calculation), and a 24% reduc-
tion in Na+. An argument can be made that Na+ (as well as Cl~) will not decline but remain in a
constant steady-state condition due to the minimal influence of soil exchange sites on Na+. We can
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28
hold Na+ constant and resolve for A13+ and the other cations. This result, shown in column 4 of
Table 4, indicates a further reduction in all cations (except Na+) but little additional change in
pH.
Now I consider a change in base saturation (BS). To estimate potential change, I took soil
chemical data, and what physical data were available [from Frank (1970) (an assumed bulk density
of 1.2 g/crn3)], calculated soil base cation (BC) content, and divided this by net base cation export
from Christophersen et al. (1982). The results (Table 5) show a value of ~20 years, so let us
assume that % BS has declined by 50% in 20 years (i.e., was 2 X its current value 20 years ago).
This is a worst case scenario since weathering is assumed to be zero.
Table 5. Soil contents vs input-output at Blrkenes
(Assumes bulk density — 1.2 g/cm3)
Soil
Iron Podzol
Iron-humus Podzol
Humus Podzol
2 BC 2 A1
keq/ha
17 85
17 180
18 79
2 BC + Al
102
197
97
(2 BC") +
BC export
19
19
20
G
(2 BC + Alat) +
BC export
Years
113
219
108
°BC = base cation. _
'Cation output minus cation input = 0.9 keq ha year .
We must then calculate Q values (neglecting exchangeable K+ and Na+ as minor or non-
changing components) as shown below:
(A?;?m;!i; - Q - (o-88)23(i°7>; = 2.58 x & . w
(m2+)3[Al3+]2 V (0.09)3(71)2
We then double % BS and calculate K:
Then the new K values are used to express total cations as a function of A13+ as in Eq. (7). The
results for a 50% change in base saturation with Na+ changing and Na+ constant are given in
columns 5 and 6 of Table 4.
Clearly, it is not possible in theory to raise pH to acceptable levels (even using this worst-case
assumption) unless other mechanisms are involved (although as Reuss noted, A13+ can change con-
siderably). This is the situation we have been debating for several years, and the calculations here
show changes of similar magnitude to those I made by "adding" SO42~ to unpolluted waters in
Alaska (Johnson 1981). The key to the problem is the change in alkalinity from positive to negative
values (or vice versa, Reuss and Johnson, in press). So far I have treated Birkenes streamwater as if
it were soil solution, but soil solution is subject to much higher pCO2. Can alkalinity develop in a
soil solution of pH 4.78 (column 5, Table 4)? Let us assume that soil pCO2 is 0.3 X 103 Pa (0.03
atm), a not-unreasonable value. Then
-------
[HC03-] -
29
KrKh pC02 _ (10-7-74)(O.Q3)
(10)
[H+]
= 33 X 10~6
jQ-4.78
= 33 Meq/L ,
Alkalinity = HCO3~ - H+ - A13+
= 33 - 17 - 11 = 5
(11)
Thus, the soil solution of pH 4.78 could have positive alkalinity and experience pH rise (and conse-
quently A13+ precipitation) upon degassing when it enters streamwater, as described by John Reuss
and Hans Martin Seip in their keynote addresses and by Reuss and Johnson (in press). In short, if
the added SO42~ to Birkenes soil solutions caused a salt-effect pH shift, such that slightly positive
alkalinity became negative, a fairly large change in stream pH could result. Whether this actually
occurred at Birkenes remains to be demonstrated (especially if organic acids are present).
An analogous analysis was carried out for the Gardsjb'n inlet (Table 6). In this case, develop-
ment of positive alkalinity by removing SO42~ is more likely, because current A13+ and H+ concen-
trations are lower than those at Birkenes:
ru™ -i _ K'-Kh PC°2 _ (10~7-74)(0.03)
[HC03 ] —- W_M
67 X 1(T6
67
Alkalinity = HCO3 - H+ - A13+
= 67 - 8 - 3 = 56 jieq/L .
Table 6. Gardsjon Inlet concentrations: Aetna! and calculated
Predicted concentration if SO42~ = 30 peq/L
No% BS° change
2X%BS° change
Ion
H+
PH
A13+
Na+
K+
Ca2+
Mg"
NH4
2) Cations
S042~
HCO3
Cl
NO3~
2 Anions
^UIICIll
cone.
19
4.7
32
209
14
94
91 (185)
3
462
181
0
232
5
418
Na+ charges
14.6
4.84
14.5
262
11
109
310
30
0
232
5
267
Na change
12
4.92
8
209
9
73
311
30
0
232
5
267
Na+ change
12
4.92
8
126
8
162
316
30
0
232
5
267
Na+ constant
8
5.09
3
209
6
84
310
30
0
232
5
267
°BS = base saturation.
UBRAHV
1X9. ENVIRONMENTAL PROTECTION AGENCY
CORVAUJS ENywOMMBTOUL RESEARCH LAB
2uO SW SSlM STREET
CORVMU
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30
It should be noted, that the lake itself has lower H+ and A13+ concentrations than the streamlets
entering it.
In summary, the key to the issue of surface water pH change according to this model is the
change in soil solution alkalinity from positive to negative (or vice versa) values, as pointed out by
Reuss. Soil solution alkalinity is determined by pCO2 and H+ and A13+ vs base cation selectivity
coefficients, none of which are conveniently measured in a survey mode. Surface water alkalinity
itself may provide a crude index, however.
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ANALYSIS BY INGVAR S. NILSSON
The following is a summary of a forthcoming paper with the title, "Why is Lake GardsjOn
acid?—An evaluation of processes contributing to soil and water acidification" (Nilsson 1984a). It
will be published in the Ecological Bulletin, Volume 37 (issued by the Swedish Natural Science
Research Council).
The average pH in the lakewater was 4.6 before liming, which took place in April 1982. Three
studies have shown that the lake was considerably less acid some decades ago. Renberg and
Hellberg (1982) showed that there has been a sudden increase of acid-tolerant diatoms in the lake
sediments, at a level which has been dated to a few decades B.P. Further evidence comes from an
inventory of chironomid remnants in the sediments (Henrikson and Oscarsson 1984), also showing a
successive increase of acid-tolerant species. Viable fish populations were reported as late as 1949,
and summer pH in the epilimnetic water was about 6.2 (Anonymous 1949, Hultberg 1984b).
The drainage area of Lake GardsjOn is 74.3 ha, the lake area being 31.2 ha. The morainic soil
has a clay content of 4 to 11%, with a mean of 5% (Melkerud 1983, Olsson et al. 1984). It is char-
acterized as an iron humus Podzol or an iron Podzol, depending on the topographical location and
the concomitant water regime. The average soil depth is only SO cm. The vegetation is dominated
by mixed coniferous forest. Norway spruce (Picea abies Karst.) is the most important tree species.
According to Olsson (1984), the site had been covered by forest for several hundred years, even
during the late 19th century and early part of the present century, when extensive areas in this part
of Sweden were still occupied by Calluna heathland. Forest cutting according to a selected system
has been practiced, however, with cattle being allowed to graze in the forest up to 1950. A large
number of dead junipers (Juniperus communis L.) are found in the forest today, which is a strong
indication of a previously more open forest. Some afforestation and clear-cutting has been under-
taken within the catchment.
A proton budget was constructed to evaluate the relative importance of the present acid deposi-
tion compared to internal proton sources (Table 7). There is a large amount of uncertainty in some
of the estimates, for instance in the estimate of the weathering rate. (The total deposition of metal-
lic cations is difficult to quantify).
Table 7. Proton budget (keq H+ ha~' year"') for the watershed
Wet deposition
SC>2 deposition
NH4+
NO3~
Accumulation of base
cations in the biomass
Dissociation of organic
acids including complex
formation
Sum
0.5
0.5
0.6-0.8
0.0
0.6
0-0.6
2.6-3.0
H+ output
NH4+ output
NOf deposition
Accumulation of anions
in the biomass
Weathering
Sum
0.5
0.0*>
0.6-0.8
0.0
1.6-2.3
2.7-3.6
''The value is <0.05-
31
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32
One proton source is not included in the table, namely the formation of organic aluminium
complexes which precipitate before they reach the stream. According to some rough calculations
this process might account for another 0.2 to 0.6 keq-ha~'-year~'. If this source is included, the
external input of free and potential acidity would account for 30-50% of the total proton load.
The proton budget indicates the extent of the current soil acidification, as do lime potential
data presented by Nilsson and Bergkvist (1983), which showed that the proton flux in the deposi-
tion was of importance for the acidification of the uppermost organic soil layer, as the average lime
potential in the stand precipitation was lower than that of the soil solution in the humus layer (1.95
against 2.11). Lime potential is here defined as pH-0.5 p(Ca+Mg). A soil chemical inventory
showed that exchangeable calcium and magnesium make up 35 and 14%, respectively, of the effec-
tive cation exchange capacity in the humus layer, while the corresponding figures for the B horizon
are 4 and 2% (Olsson et al. 1984). Although most of the net output of base cations in the runoff
water should result from weathering processes (cf. Bache 1983), a certain net loss of exchangeable
base cations is likely in the humus layer because of the lime potential gradient and because of the
relatively high calcium and magnesium saturation. Such a loss should be of considerably less
importance in the mineral soil, at least in absolute terms, as the selectivity for an individual cation
usually increases with a decreasing share of the cation exchange capacity (CEC) (Wiklander and
Andersson 1972, Wiklander 1980).
As pointed out by Seip (1980) and others, soil acidification per se will not cause surface water
acidification unless there is also an increased flux of mobile anions.
An important question is whether an increasing flux of sulfate, for example, could be a suffi-
cient explanation of the fairly recent lake acidification. One way to deduce the pH value in the lake
water at a different sulfate concentration is to insert the present proportionality constant between
H+ and SO42~. A 50% reduction of the sulfate concentration would, according to this simplistic
analysis, increase the pH to 4.9 to 5.0. This pH interval is still a bit too low for the carbonic acid
system to become important. It is evident both from this approach, and from the more sophisticated
one used by Dale Johnson, that soil acidification has played a crucial role in the lake acidification
process.
The actual significance of the present atmospheric deposition can be further illustrated by
making a proton budget for the lake, which is shown in Table 8. It is essentially based on data
reported by Grennfelt et al. (1984) and Hultberg (1984a). The atmospheric proton flux, as in the
Table 8. Proton budget for Lake
Gardsjtin, based on the lake area.
The contribution from the
drainage area is estimated
from extrapolation of fluxes
measured in the three small
ganged microcatchments
H+(keqha 'year ')
Wet deposition
SO2 deposition
Main inlet
Drainage area
Main outlet
Calculated
Proton retention
0.50
0.43
0.44
0.74-1.15
0.94
1.17-1.58
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33
"terrestrial" proton budget, consists of H+, as measured in the wet deposition, plus the H+ result-
ing from the conversion of dry-deposited SO2 to H2SO4. Depending on how the flux from the drain-
age area is estimated (the lower value of the range being obtained from an extrapolation of the H+
flux measured in a partly clear-cut subwatershed), the direct deposition on the lake surface
accounts for 37 to 44% of the proton input to Lake GardsjOn.
The recent acidification of Lake Gardsjtin is likely to have been caused by a combination of
direct atmospheric deposition on the lake surface and an increased flux of protons and aluminum
from the drainage area. This latter increase seems to be caused by an increase of the sulfate flux
and by soil acidification, both processes being significantly influenced by the atmospheric deposi-
tion.
-------
SOIL SENSITIVITY CRITERIA
R. S. Turner and D. W. Johnson
Oak Ridge National Laboratory
Oak Ridge, Tennessee
During the session on "Soil Acidification," John Reuss listed several effects of soil acidifica-
tion, including cation depletion, aluminum mobilization, change in soil pH (ApH/AH+), and base
cation loss from calcareous soils. Egbert Matzner suggested using a broader measure such as a
decrease in acid neutralizing capacity. It was suggested that that would involve a capacity factor so
large as to make no soils sensitive. What are needed are more-specific capacity factors such as
exchangeable cations or intensity factors such as solution pH depression and aluminum mobiliza-
tion. Jeff Lee pointed out that looking at specific soil acidification factors may be too narrow; what
are needed, at least for assessment purposes, are criteria that would tell us "what are sensitive
forests." At the end of the discussion Dale Johnson agreed to outline his thoughts on sensitivity cri-
teria (Table 9) that could be used as a basis for further discussion.
Results of the discussion at the "Soils Sensitivity Criteria" session are summarized in Table 10.
The consensus was that the sensitivity criteria could be broken down into capacity and intensity fac-
tors. However, it was pointed out that, to be useful, capacity factors had to be expressed as capacity
over rate. For a capacity factor to be a good indicator of sensitivity, we need to know how long it
Table 9. SensitMty criteria
Receptor
Solid phase
Solution phase
Soils (solid phase)
Capacity factors
Reduction in % BS
S(>42 -retention
NC>3 -retention
Waters (soil solution and
surface water)
Intensity factors
A13+ mobilization
pH depression
Organisms
Forest damage
Fish kill
Low CEC, moderate
% BS (Wiklander
1980), weathering
Fe + Al oxides,
organic matter
Nitrification potential,
C/N ratio, forest
production
Low%BS
% BS, pCO2)
selectivity coefficients
Ionic strength
Alkalinity
— Mechanisms unknown —
Water chemistry?
34
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35
Table 10. Sensitivity criteria
as revised during the workshop session
Soil (solid phase) capacity factors—all need to be expressed
as capacity/rate to give time until "damage"
Reduction in Low CEC (independent of CEC over the
base saturation (BS) long term)
Moderate initial BS (independent of
initial BS over the long term)
Low weathering (base cation replace-
ment) rate
Reduction in cation pH
exchange capacity (CEC) Clay mineralogy
SC>4 retention Fe and Al oxide crystallinity
(inorganic) Organic matter
P" 2-
SC>4 concentration in solution
Organic S retention Microbial processes
High organic matter buildup
SO42~ reduction Anaerobic conditions
NOjT retention Nitrification potential
Nitrification inhibitors
C/N ratio (weak predictor)
Forest productivity
Forest type
Litterfall rate
Decomposition rate
Climatic factors
NH4+ retention CEC
Soil solution and surface water intensity factors—these
factors potentially cause "damage* when one or more of the
capacity factors is exhausted
pH depression pCO2
BS
Cation selectivity coefficient
Low alkalinity alone not suitable
surrogate
A13+ mobilization Low BS, low pH
High ionic strength (mobile anions)
Presence and solubility of Al mineral
Organic matter complexing
Paniculate transport to waterbody
will take to exhaust the capacity, or how long it will be until enough capacity is exhausted that the
intensity factors will be affected. This led to discussions of little known variables such as weathering
rates, biological uptake, and cycling rates of some of the elements. Thus, it was recognized that,
while we can identify numerous capacity factors that may affect sensitivity of a soil to acidic depo-
sition, we do not know enough about the biogeochemical process rates associated with those factors
to be able to tell how near we are to exhausting the capacity of many of the factors listed. The spe-
cific research needs mentioned included effects on weathering by organic and mineral acids, biologi-
cal interactions of sulfur, and a better clarification of nitrification mechanisms. Also needed is a
better understanding of hydrologic flow routes through the soil, and potential differences between
macropore and bulk soil chemistry and rates of change.
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36
Very limited discussion was directed toward specifying soil sensitivity criteria for forest damage
or for fish kills. Because so little is known about the mechanistic relationships between forest dam-
age and acidic deposition, participants were reluctant to suggest which soil factors would be useful
sensitivity criteria. The consensus was that the subject should be discussed more fully at another
workshop. The most direct indicator of hazard to fishes was thought to be the ratio of Al to Ca in
surface water. Concentrations of these elements could be dependent, to one degree or another, on
most of the soil sensitivity factors listed.
The sensitivity criteria listed in Tables 9 and 10 are based on known soil chemical and physical
properties (as they relate to the movement of SO42~ and NO3~ through soils) and on the rate at
which soil and soil solution acidity will change in response to SO42~ and NO3~ leaching. A reduc-
tion in base saturation occurs most easily in soils with a moderate % base saturation (% BS) (so
that the yield of base cations per unit H+ input, or M/H+, is near 1.0) and low exchangeable
reserves, which translates into moderate % BS and low CEC. This is essentially the view espoused
by Wiklander (1980). According to the best available evidence, SO42~ retention of is related to Fe
+ Al oxide and organic matter content (Johnson and Todd 1983). Retention of NO3~ is governed
by ecosystem nitrogen status, which in turn is related to tree nitrogen uptake, soil microbial nitro-
gen demand, and nitrification potential (Vitousek et al. 1979). Very broad sensitivity criteria would
include tree nitrogen uptake by forest type and soil C/N ratio overlaid on atmospheric deposition
rate.
For waters, we are interested in solution H+ and A13+ concentration, both of which are inten-
sity factors determined both by capacity factors (% BS, selectivity coefficients) and intensity factors
(pCO2, ionic strength, alkalinity). See the keynote address by Reuss for details.
The sensitivity criteria discussed up to this point relate to soil and solution chemistry only and
not to biological effects. In terms of fish, the consensus was that the relationship between chemical
and biological effects are relatively straightforward (i.e., fish damage = f (water chemistry). In
terms of forest damage, we do not know appropriate toxicity levels for A13+ yet nor, in a broader
sense, do we know that A13+ mobilization is the cause of observed forest dieback and decline. Thus,
the link between acid deposition and forest damage (if any).has not been established and, therefore,
sensitivity criteria cannot be assigned except insofar as they represent hypothesized mechanisms. In
terms of the latter, the A13+ and N-saturation hypotheses would be defined as in Tables 9 and 10.
It must be emphasized, however, that the assignment of forest damage sensitivity criteria is prema-
ture at best and misleading at worst until mechanisms of forest damage are established. The latter
will require more research and more time to sort out; it has taken well over a decade to sort out
appropriate mechanisms for water acidification.
-------
ACKNOWLEDGMENTS
This research was funded as part of the National Acid Precipitation Assessment Program by
the U.S. Environmental Protection Agency under Interagency Agreement No. 40-1353-83 with the
U.S. Department of Energy under Contract No DE-AC05-84OR21400 with Martin Marietta
Energy Systems, Inc.
J. O. Reuss' contribution was sponsored in part by the U.S. Environmental Protection Agency.
The research described in this article has been funded in part by the EPA/NCSU Acid Precipita-
tion Program (a cooperative agreement) between the U.S. Environmental Protection Agency and
North Carolina State University. It has not been subjected to EPA's required peer and policy
review and therefore does not necessarily reflect the views of the Agency and no official endorse-
ment should be inferred. Publication No. 2369, Environmental Sciences Division, ORNL.
37
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LIST OF ATTENDEES
Goran I. Agren
Swedish University of Agricultural Sciences
Uppsala, Sweden
Ernesto Bosatta
Swedish University of Agricultural Sciences
Uppsala, Sweden
Nils Christophersen
Central Institute for Industrial Research
Forskningsv. 1, Blindern
Oslo 3, Norway
Roger Clapp
Environmental Sciences Division
Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831
Dale W. Cole
College of Forest Resources
University of Washington
Seattle, Washington 98195
Christopher S. Cronan
Land and Water Resources Center
University of Maine
Orono, Maine 04469
P. J. Dillon
Ontario Ministry of Environment
Box 39
Dorset, Ontario POA 1EO
Canada
Jerry W. Elwood
Environmental Sciences Division
Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831
Folke O. Andersson
Swedish University of Agricultural Sciences
Uppsala, Sweden
Paul Buldgen
University of Liege
Department of Botany
Sart Tilman, B-4000 Liege
Belgium
Robbins M. Church
U.S. Environmental Protection Agency
200 SW 35th Street
Corvallis, Oregon 97377
B. J. Cosby
Department of Environmental Sciences
Clark Hall
University of Virginia
Charlottesville, Virginia 22901
Mark B. David
U.S. Environmental Protection Agency
200 SW 35th Street
Corvallis, Oregon 97333
Charles Driscoll
238 Hinds Hall
Department of Civil Engineering
Syracuse University
Syracuse, New York 13210
Neil Foster
90 Florwin Drive
Canadian Forestry Service
Sault Ste. Marie
Ontario, Canada
42
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43
James Galloway
Clark Hall
University of Virginia
Charlottesville, Virginia 22903
Michael Hauhs
Institute of Soil Science and Forest
Nutrition
Busgenweg 2
34 Gottingen, West Germany
John W. Huckabee
Electric Power Research Institute
3412 Hillview
Palo Alto, California 94091
Dale W. Johnson
Environmental Sciences Division
Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831
Jeffrey Lee
U.S. Environmental Protection Agency
200 SW 35th Street
Corvallis, Oregon 97333
John Malanchuk
Acid Deposition Assessment Staff
RD-676
U.S. Environmental Protection Agency
Washington, D.C. 20460
Jan Mulder
Department of Soil Science and Geology
Agricultural University of Wageningen
Duivendaal 10
Wageningen, The Netherlands
Stephen C. Nodvin
University of California-Riverside
Route 1, Box 198
Mammoth Lakes, California 93546
Dan D. Richter
Environmental Sciences Division
Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831
Robert Goldstein
Electric Power Research Institute
P.O. Box 10412
Palo Alto, California 94303
George M. Hornberger
Department of Environmental Science
Clark Hall
University of Virginia
Charlottesville, Virginia 22903
Hans Hultberg
Swedish Environmental Research Institute
P.O. Box 5207
Gothenburg, Sweden
J. M. Kelly
TVA/ORNL Watershed Program
Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831 .
David Lam
Environment of Canada, CCIW
867 Lakeshore Road
Burlington, Ontario LTR 4A6
Canada
Egbert Matzner
University of Gottingen
Busgenweg 2
Gottingen, West Germany 0551
Ingvar Nilsson
Department of Ecology and Environmental
Research
Swedish University of Agricultural Science
Uppsala, Sweden S-75007
John O. Reuss
Department of Agronomy
Colorado State University
Fort Collins, Colorado 80523
Hans M. Seip
Central Institute for Industrial Research
Forskningsv. 1, Box 350
Blindern, Oslo 3, Norway
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44
Helgan Van Miegroet
College of Forest Resources, AR-10
University of Washington
Seattle, Washington
Ulf Wahlgren
Swedish Environmental Research Institute
Vikingavagen 5
Sollentuna, Sweden
Richard Skeffington
Central Electricity Generating Board
Kelvin Avenue
Leatherhead, Surrey KT22
England
Robb S. Turner
Environmental Sciences Division
Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831
Webb Van Winkle
Environmental Sciences Division
Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831
Dick Wright
Clark Hall
University of Virginia
Charlottesville, Virginia 22903
Arne O. Stuanes
Norwegian Forest Research Institute
P.O. Box 61
N-1432 AAS-NLH
Norway
Hans Van Grinsven
Department of Soil Science & Geology
Wageningen
The Netherlands
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ORNL/TM-9258
INTERNAL DISTRIBUTION
1. S. I. Auerbach 17. R. J. Olson
2. E. A. Bondietti 18, D. E. Reichle
3. R. B. Clapp 19. D. S. Shriner
4. N. H. Cutshall 20. R. S. Turner
5. J. W. Elwood , 21. W. Van Winkle
6. S. G. Hildebrand 22. Central Research Library
7-11. D. W. Johnson 23-37. ESD Library
12. J. M. Kelly 38-39. Laboratory Records Dept.
13. G. M. Lovett 40. Laboratory Records, ORNL-RC
14. R. J. Luxmoore 41. ORNL Patent Office
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EXTERNAL DISTRIBUTION
43. Goran I. Agren, Swedish University of Agricultural Science, Uppsala, Sweden S-75007
44. Folke Q. Andersson, Swedish University of Agricultural Science, Uppsala, Sweden S-
75007
45. Ann Bartusky, EPA/NCSU Acid Precipitation Program, North Carolina State Univer-
sity, Raleigh, NC 27606
46. Ernesto Bosatta, Swedish University of Agricultural Science, Uppsala, Sweden S-75007
47. Paula Buldgen, University of Liege, Department of Botany, Sart Tilman, B-4000 Liege,
Belgium
48. J. Thomas Callahan, Associate Director, Ecosystem Studies Program, Room 336, 1800 G
Street, NW, National Science Foundation, Washington, DC 20550
49. Nils Christophersen, Central Institute for Industrial Research, Forskningsv. 1, Blindern,
Oslo 3, Norway
50. Robbins M. Church, U.S. Environmental Protection Agency, 200 SW, 35th Street, Cor-
vallis, OR 97377
51, Dale W. Cole, University of Washington, College of Forest Resources, Seattle, WA
98195
52. B. J. Cosby, University of Virginia, Clark Hall, Department of Environmental Science,
Charlottesville, VA 22901
53. Ellis Cowling, School of Forest Resources, North Carolina State University, Raleigh, NC
27650
54. Christopher S. Cronan, University of Maine, Land and Water Resources Center, Orono,
MA 04469
55. R. C. Dahlman, Carbon Cycle Program Manager, Carbon Dioxide Research Division,
Office of Energy Research, Room J-311, ER-12, Department of Energy, Washington,
DC 20545
45
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56. Mark B. David, U.S. Environmental Protection Agency, 200 SW, 35th Street, Corvallis,
OR 97333
57. P. J. Dillon, Ontario Ministry of Environment, Box 39, Dorset, Ontario, Canada POA
1EO
58. Charles Driscoll, Syracuse University, 238 Hinds Hall, Department of Civil Engineering,
Syracuse, NY 13210
59. Ivan Fernandez, University of Maine, Orono, ME 04469
60. G. J. Foley, Office of Environmental Process and Effects Research, U.S. Environmental
Protection Agency, 401 M Street, SW, RD-682, Washington, DC 20460
61. Neil Foster, Canadian Forestry Service, 90 Florwin Drive, Sault Ste. Marie, Ontario,
Canada
62. James Galloway, University of Virginia, Clark Hall, Charlottesville, VA 22903
63. J. H. Gilford, U.S. Environmental Protection Agency, Office of Toxic Substances, 401 M
Street, SW, TS-796, Washington, DC 20460
64. Robert Goldstein, EPRI, P.O. Box 10412, Palo Alto, CA 94303
65. Michael Hauhs, Institute of Soil Science and Forest Nutrition, Busgenweg 2, 34 Got-
tingen, West Germany
66. George M. Hornberger, University of Virginia, Department of Environmental Science,
Clark Hall, Charlottesville, VA 22903
67. J. W. Huckabee, Project Manager, Environmental Assessment Department, Electric
Power Research Institute, 3412 Hillview Avenue, P.O. Box 10412, Palo Alto, CA 94303
68. Hans Hultberg, Swedish Environmental Research Institute, P.O. Box 5207, Gothenburg,
Sweden
69. F. A. Koomanoff, Director, Carbon Dioxide Research Division, Office of Energy
Research, Room J-311, ER-12, U.S. Department of Energy, Washington, DC 20545
70. David Lam, Environment of Canada, 867 Lakeshore Road, Burlington, Ontario, Canada
L7R4A6
71. Jeffrey Lee, USEPA, 200 SW, 35th Street, Corvallis, OR 97333
72. Rick Linthurst, Kilkelly Environmental Associates, P.O. Box 31265, Raleigh, NC 27622
73. John Malanchuk, USEPA, Acid Deposition Assessment Staff, RD-676, Washington, DC
20460
74. Egbert Matzner, University of Gottingen, Busgenweg 2, Gottingen, West Germany 0551
75. Helen McCammon, Director, Ecological Research Division, Office of Health and
Environmental Research, Office of Energy Research, MS-E201, ER-75, Room E-233,
Department of Energy, Washington, DC 20545
76. Harold A. Mooney, Department of Biological Sciences, Stanford University, Stanford,
CA 94305
77. Jan Mulder, Department of Soil Science & Geology, Agricultural University, Wagen-
ingen, Duivendaal 10, Wageningen, The Netherlands
78. Ingvar Nilsson, Dept. of Ecology and Environmental Research, Swedish University of
Agricultural Science, Uppsala, Sweden S-75007
79. Dr. Stephen C. Nodvin, University of California-Riverside, Route 1, Box 198, Mammoth
Lakes, CA 93546
80. Williams S. Osburn, Jr., Ecological Research Division, Office of Health and Environmen-
tal Research, Office of Energy Research, MS-E201, EV-33, Room F-216, Department of
Energy, Washington, DC 20545
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47
81. E. M. Preston, Corvallis Environmental Research Laboratory, U.S. Environmental Pro-
tection Agency, 200 SW 35th Street, Corvallis, OR 97333
82. Irwin Remson, Department of Applied Earth Sciences, Stanford University, Stanford,
CA 94305
83-87. John Reuss, Department of Agronomy, Colorado State University, Fort Collins, CO
80523
88. Gerald Schnoor, Engineering Bldg., University of Iowa, Iowa City, IA 52242
89. Hans M. Seip, Central Institute for Industrial Research, Forskningsv. 1, Box 350, Blin-
dern, Norway
90. Richard Skeffington, Central Electricity Generating Board, Kelvin Avenue, Leatherhead,
Surrey KT22, England
91. R. J. Stern, Director, Office of Environmental Compliance, MS PE-25, FORRESTAL,
U.S. Department of Energy, 1000 Independence Avenue, SW, Washington, DC 20585
92. Arne O. Stuanes, Norwegian Forest Research Institute, P.O. Box 61, N-1432 AAS-
NLH, Norway
93. Hans Vans Grinsven, Department of Soil Sciences and Geology, Wageningen, The Neth-
erlands
94. Helgan Van Miegroet, University of Washington, College of Forest Resources, AR-10,
Seattle, WA
95. Ulf Wahlgren, Swedish Environmental Research Institute, Vikingavagen 5, Sollentuna,
Sweden
96. Raymond G. Wilhour, Chief, Air Pollution Effects Branch, Corvallis Environmental
Research Laboratory, U.S. Environmental Protection Agency, 200 SW 35th Street, Cor-
vallis, OR 97330
97. Frank J. Wobber, Division of Ecological Research, Office of Health and Environmental
Research, Office of Energy Research, MS-E201, Department of Energy, Washington,
DC 20545
98. M. Gordon Wolman, The Johns Hopkins University, Department of Geography and
Environmental Engineering, Baltimore, MD 21218
99. Robert W. Wood, Director, Division of Pollutant Characterization and Safety Research,
U.S. Department of Energy, Washington, DC 20545
100. Dick Wright, University of Virginia, Clark Hall, Charlottesville, VA 22903
101. Office of Assistant Manager for Energy Research and Development, Oak Ridge Opera-
tions, P.O. Box E, U.S. Department of Energy, Oak Ridge, TN 37831
102-128. Technical Information Center, Oak Ridge, TN 37831
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