On September 4, 1984, Brian Mulroney was' elected Prime Minister of. Canada. He promised a new era of close Canada-U.S. relations and brought a reputation ...
ATMOSPHERIC DEPOSITION
TITLES RECENTLY PUBLISHED BY IAHS Proceedings of the symposia held during the Second IAHS Assembly, Budapest, July 1986: Modelling SnowmcilTnduccd Processes Publ.no.155 (1986), price $40 Conjunctive Water Use Pubf.no. 156 (1986), price S48 Monitoring to Detect Changes in Water Quality Scries I'ubl.no.157 (1986), price $40 Integrated Design of Hydrological Networks Publ.no.158 (1986), price $40 Drainage Basin Sediment Delivery. Publ.no.159 (19S6), price S45
Proceedings of the Albuquerque Symposium, August 1986
Hydrologie Applications of Space Technology. Publ.no.160 (1986), price $45
Proceedings of the Cocoa Beach Workshop, August 1985
Karst Water Resources. Proceedings of the Ankara Symposium, July 19S5 Publ.no.161 (1986), price $45 Avalanche Formation, Movement and Effects. Publ.no.162 (1987), price $50
Proceedings of the Davos Symposium, September 1986
Developments in the Analysis of Groundwater Flow Systems. International Commission on Groundwater Publ.no.163 (1986), price $35 Water for the Future: Hydrology in Perspective. Publ.no.164 (1987), price $50 Erosion and Sedimentation in the Pacific Rim. Publ.no.165 (1987), price $55
Report prepared by a Working Group of the IAHS
Proceedings of the Rome Symposium, April 1987 Proceedings of the Corvallis Symposium, August 1987
Proceedings of the symposia held during the IUGG Assembly, Vancouver, August 1587 Large Scale Effects of Seasonal Snow Cover Publ.no.166 (1987), price $42 Forest Hydrology and Watershed Management Pubi.no.167 (1987), price $55 The Influence of Climate Change and Climatic Variability on the Hydrologie Regime and Water Resources Publ.no.168 (1987), price $55 Irrigation and Water Allocation Publ.no. 169 (1987), price S32 The Physical Basis of Ice Sheet Modelling Publ.no.170 (1987), price $40 Hydrology 2000. Report of the IAHS Hydrology 2000 Working Group PubI.no.T71 (1987), price $22 Side Effects of Water Resources Management. Publ.no.172 (1988), price $40
Report prepared by an IHP-III Working Group
Sediment Budgets. Proceedings of the Porto Alegre Symposium, December 1988 Publ.no.174 (1988), price $60 Consequences of Spatial Variability in Aquifer Properties and Data Limitations for Groundwater Modelling Practice. Report prepared by a Working Group of the International Commission on Groundwater Publ.no.175 (1988), price $45 Karst Hydrogcology and Karst Environment Protection. Proceedings of the IAH/IAHS Guilcn Symposium, October 1988 Publ.no. 176 (1988), price $55 Estimation of Arcal Evapotranspiration. Proceedings of Workshop HW3 held during the IUGG Assembly, Vancouver, August 1987 Publ.no.177 (1989), price $45 FRIENDS in Hydrology. Proceedings of the Bolkcsjo Symposium, April 1989 I'ubl.no.187 (1989), price $50 PLEASE SEND ORDERS AND/OR ENQUIRIES TO: Office of the Treasurer Bureau des Publications de IAHS Press, Institute of IAHS, 2000 Florida Avenue rUGGI,140RuedcGrcncIIc Hydrology, Wallingford NW, Washington 7S700 Paris, France Oxfordshire OX10 8 B C U K DC 20009, USA [telephone: 45 SO 34 95 ext. 816; [telephone: (0)49138800; [telephone: 202 462 6903] telex: 204989 igngnlf (Attn: UGC1)] telex: 849365 hydrolg] A copy of a catalogue of IAHS publications and information on individual membership of IAHS may be obtained free of charge from any of these addresses.
ATMOSPHERIC DEPOSITION
Edited by J A C Q U E S W. D E L L E U R School of Civil Engineering Purdue University, West Lafayette Indiana 47907, USA
Proceedings of a symposium held during the Third Scientific Assembly of the International Association of Hydrological Sciences at Baltimore, Maryland, USA, May 1989. The symposium was sponsored by the United Nations Environment Programme, the United Nations Education, Scientific and Cultural Organization and the World Meteorological Organization.
IAHS Publication No. 179
Published by the International Association of Hydrological Sciences 1989. IAHS, Institute of Hydrology, Walling ford, Oxfordshire OX10 8BB, UK. IAHS Publication No. 179. ISBN 0-947571-86-8
The designations employed and the presentation of material tnrougnout the publication do not imply the expression of any opinion whatsoever on the part of IAHS concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The use of trade, firm, or corporate names in the publication is for the information and convenience of the reader. Such use does not constitute an official endorsement or approval by IAHS of any product or service to the exclusion of others that may be suitable.
ACKNOWLEDGEMENTS The Editor wishes to thank the authors for their compliance with the deadlines and their acceptance of the editorial revisions. I am particularly thankful to Kamie Redinbo who typed all the papers and whose mastery of the word processor resulted in an elegant volume. I am also indebted to Edward Haslam, Barbara I. Schmidt, graduate students at Purdue University, for their assistance in proof reading and to Christine Sweet of NÔAA for her assistance with the papers that required special editing.
Printed in Great Britain by Galliard (Printers) Ltd, Great Yarmouth
Preface The atmosphere operates as a reservoir or vessel in which numerous chemical reactions t a k e place and in which the wind transports these compounds over hundreds to thousands of kilometers. Although oxygen, carbon dioxide, nitrogen and sulfur compounds are released by n a t u r a l processes, the large scale discharge of sulfur dioxide and nitrogen oxides in the atmosphere come from anthropogenic sources. Sulfuric and nitric acids are formed and very high acidities are found at the base of clouds. Acid rain a n d dry sulfates and other particles reach the ground and the vegetation. These wet and dry depositions undergo physical and chemical changes as they progress through the terrestrial phase of the hydrological cycle. If the soil is limestone rich, or otherwise alkaline, then it will neutralize the acid deposition. If the soil is slightly acid and lacks the capacity to immobilize the acids by retention or cation exchange the runoff is as acidic as the rain t h a t produces it. Runoff from frozen or saturated soil or from bare granite rock is not affected by soil processes, and snowmelt often results in peaks of acidity in streams. Lake water may contain some basic ions derived from rock weathering t h a t can neutralize the acid runoff. If a lake lacks such acid-neutralizing capacity, then it may acidify immediately. Research efforts have recently concentrated on regional transport and atmospheric chemistry of pollutants and on the effect of acid deposition on ecosystems. These proceedings cover many of these research aspects, but does n o t a t t e m p t to be exhaustive. Global and regional modeling of acid deposition and removal rates are discussed in the first section. Though the problem of control of acid deposition is principally a political one, this is discussed in the second section (i.e. conflict analysis and systems analysis are techniques used in the study of abatement strategies). After this broad brush painting of the scientific and political problems associated with acid deposition, Sections III and IV concentrate on the measurement and composition of acid deposition. Statistical analysis in Section V is used to understand the variations in precipitation chemistry, or in the determination of the sources of deposition, etc. The next two sections deal with the écologie impacts of acid deposition, Section VI specializes on the hydrologie response to acid deposition while Section VII presents research studies on the effect of acid deposition on forest and canopy. This symposium was jointly organized by the International Association of Hydrological Sciences, the American Geophysical Union and by the International Association of Meteorology and Atmospheric Physics. The support of these scientific organizations is gratefully acknowledged.
Convenor.
Co-convenor:
J.W. DELLEUR School of Civil Engineering Purdue University West Lafayette, IN 47907 USA J.M. MILLER NOAA-Air Res. Lab (R/E/AR) 8060 13th Street, Room 927 Silver Springs, MD 20910 v
Contents
Preface
J.W. Délient & J.M Miller
v
1 GLOBAL M O D E L I N G OF D E P O S I T I O N AND ACID REMOVAL R A T E S Simulated Global Deposition of Reactive Nitrogen Emitted by Fossil Fuel Combustion Hiram Levy, II Comparison of Parameterized Nitric Acid Removal Rates Using A Coupled Stochastic - Photochemical Tropospheric Model Richard W. Stewart, Ann M Thompson and Melody A. Owens
3
11
2 REGIONAL MODELING OF ACID D E P O S I T I O N AND ABATEMENT STRATEGIES Modeling the Formation and Deposition of Acidic Pollutants Chris J. Walcek and Julius.S. Chang
21
Application of Conflict Analysis in Determining Acid Rain Abatement Strategies Edward A. McBean, N. Okada, K. Hipel & T. Unny
27
Acid Rain Control Strategies from Multiple Long Range Transport Models /. Hugh Ellis
37
3 M E A S U R E M E N T O F P R E C I P I T A T I O N AND D E P O S I T I O N Precipitation Data Compatibility in North America and the Impact on Studies of Acid Deposition B.E. Goodison & R.J. Vet
47
WMO Solid Precipitation Measurement Intercomparison: Objectives, Methodology, Analysis B.E. Goodison, B. Sevruk & S. Klemm
57
Wind Field Deformation Above Precipitation Gage Orifices Boris Sevruk, Jacques A. Hertig & Roman Spiess
65
Monitoring Atmospheric Deposition in California's Sierra Nevada: A Comparison of Methods Bruce J. McGurk, Neil Berg, D. Marks, John M Melack, Frank Setaro
71
4 C O M P O S I T I O N OF ACID D E P O S I T I O N The Chemical Composition of Precipitation, Dew and Frost and Fog in Denver, Colorado Leroy J. Schroder, Timothy C. Willoughby, Randolph B. See & Barnard A. Malo
83
Distribution, Chemical and Isotopic Characteristics of Precipitation Events in an Arid Environment - Makhtesh Ramon Basin, Israel Ronit Nativ
91
Comparison of Ionic Composition of Cloudwater Within and Above the Canopy of an Above Cloudbase Forest Thomas P. DeFelice
101
V l l l
Contents
Tritium Deposition Over the Continental United States, 1953-1983 Robert L. Michel
109
5 ACID D E P O S I T I O N AS A S T O C H A S T I C P R O C E S S The Use of Atmospheric Transport P a t t e r n Recognition Techniques in Understanding Variation in Precipitation Chemistry Jennie L. Moody, Julie A. Galusky and James N. Galloway
119
The Applicability of Principal Components Analysis for Determining Sources of Wet Deposition Richard P. Hooper & Norman E. Peters
127
Information Content Evaluation for Acid Deposition Network Remediation John R. Donald & Edward A. McBean
137
Stochastic Modeling of Rainfall Processes in the Central African Tropics T.C. Sharma
145
6 HYDROLQGIC I M P A C T OF ACID DEPOSITION Regional Simulation of Surface Water Acidification: Uncertainty Due to Specification of Atmospheric Deposition B.J. Cosby, CM. Hornberger, & R.F. Wright
153
Systematic Parameter Estimation Strategy for Refining the Birkenes Model J.W. Delleur & Fi-John Chang
163
Atmospheric Deposition of Sulfur to a Granite Outcrop in the Piedmont of Georgia, USA Norman E. Peters
173
La deposition atmosphérique et le coefficient de lessivage des nutrients Jôzsef Déri
183
7 E F F E C T OF ACID DEPOSITION ON F O R E S T AND CANOPY Contribution of Acidic Deposition on High Elevation Forest Canopy to the Hydrologie Cycle V.K. Saxena and N.H. Lin
193
Effects of Forest Canopy on Throughfall Precipitation Chemistry Peter Kloeti, II.M. Keller & M. Guecheva
203
Foliar Absorption of I ô N Labeled Nitric Acid Vapor (HN0 3 ) in Mature Eastern Pine (Pinus strobus L.) James AI Vose, Wayne T. Swank, Randolph W. Taylor, William. V. Dashek, & Arthur L. Williams
211
Bulk Precipitation Deposition of Inorganic Chemicals in Forest Areas and its Influence on Water Quality in the Federal Republic of Germany Horst-Michael Brechtel
221
The Effects of Acid Rain and Forest Die-Back on Groundwater Case Studies in Bavaria,Germany (FRG) Thomas Haarhoff
229
Contents
IX
8 DEPOSITION AND PRECIPITATION The Leaching of Strong Acid Anions from Snow During Rain-on-Snow Events: Evidence for Two Component Mixing KG. Jones, M Tranter & T.D. Davits
239
Mixing of Acid Meltwater with Groundwater in a Forested Basin in Finland Lars Bengtsson, Ahti Lepisto, Rafinder K. Saxena & Pertti Seuna
251
Application of the Step-Duration Orographic Intensification Coefficient Method to the Estimation of Orographic Effects on Rainfall Lin Bingzhang
259
Hydrometeorological Characteristics of the Tibet Plateau Liu Guowei
267
Analysis of Diabatic Wind and Temperature Profiles Over the Amazonian Forest //. Viswanadham, V.P. Silva Filho, A.O. Manzi & L.D.A. Sa
281
Global Modeling of Deposition and Acid Removal Rates
Atmospheric Deposition (Proceedings of the Baltimore Symposium, May 1989). IAHS Publ. No. 179.
SIMULATED GLOBAL DEPOSITION OF REACTIVE N I T R O G E N E M I T T E D B Y FOSSIL F U E L C O M B U S T I O N Hiram L e v y II Geophysical Fluid Dynamics Laboratory/NOAA, Box 308, Princeton, NJ 08542
Princeton
University
P.O.
ABSTRACT We use the medium resolution (265 km horizontal grid) Geophysical Fluid Dynamics Laboratory (GFDL) general circulation transport model to simulate the global deposition of reactive nitrogen emitted by fossil fuel combustion. The nitrogen species are transported as a single tracer, the global parameter for wet deposition is based on the observed wet deposition of nitrogen over North America, and constant bulk coefficients for dry deposition over land and sea are pre-calculated from measured concentrations and deposition velocities. The simulated yearly wet depositions in Europe, as well as nearby and distant export sites, are in reasonable agreement with observations. The agreement is generally quite good and almost always within a factor of 2. No more than 1.4 Tg of the 21.3 Tg of nitrogen emitted by fossil fuel combustion are deposited in the Southern Hemisphere, yet this source accounts for less than 10% of the apparent background deposition. The 4 Tg of nitrogen exported by the three major source regions (US/Canada, Europe, and Asia) accounts for most of the deposition over the remote Northern Hemisphere. The simulated deposition over the North Pacific, which is in good agreement with estimates based on recent observations, is dominated by emissions from Asia, while U S / C a n a d i a n emissions dominate deposition over the North Atlantic. INTRODUCTION The largest source of reactive nitrogen in the global nitrogen cycle, fossil fuel combustion, results in an estimated yearly global source of 21xl0 12 grams of nitrogen (21 Tg N) (Logan, 1983). This surface source greatly exceeds the other documented global source, stratospheric injection, which has a range of 0.5 - 1.0 Tg N (Levy et al., 1980). While a number of other sources have been suggested, [lightning, biomass burning, microbial activity], estimates of their global contribution are quite uncertain and none are currently thought to be as important as fossil fuel combustion (e.g. Logan, 1983). A medium resolution [265 km grid] general circulation transport model (Mahlman and Moxim, 1978) is used to simulate the global deposition of nitrogen resulting from fossil fuel combustion. The resulting climatology is needed to study the cumulative impact of fossil fuel combustion on regional environments and the global nitrogen budget. First, we compare the model's deposition with available observations. Individual contributions from major source regions are then identified and the contribution of NOx emissions from fossil fuel combustion to the nitrogen budget of the Southern Hemisphere is determined. 3
Hiram Levy II
4
MODEL DESCRIPTION The global transport model (Mahlman & Moxim, 1978), which has already been used to demonstrate the important role of dry deposition in acid deposition over North America (Levy & Moxim, 1987) and the impact of combustion nitrogen on the global nitrogen budget (Levy & Moxim, 1989), has 11 levels, a horizontal grid size of 265 km, a time step of 26 minutes, and uses the 6 hour time-average winds and precipitation provided by a parent general circulation model (GCM) (Manabe & Holloway, 1975; Manabe et al., 1974). This GCM generates an ensemble of realistic weather p a t t e r n s t h a t compares well with observed yearly climatology and with observed meteorology on time scales ranging from six hour synoptic events to seasonal cycles. The collection of gaseous and particulate reactive nitrogen compounds that, result from the combustion emissions are transported as a single tracer, NOy. This tracer satisfies the following equation: ^ ^ -
= TRANSPORT + SOURCE - Dp*R - # * R
W
at where R is the NOy volume mixing ratio, p* is surface pressure, D is the dry deposition coefficient, and is the precipitation removal coefficient. The formulation of TRANSPORT, which represents flux convergence resulting from both the resolved air motions and sub-grid scale diffusion, has already been described (Levy and Moxim, 1987; Levy and Moxim, 1989; Mahlman and Moxim, 1978). The global source of NOx resulting from fossil fuel combustion, SOURCE, has been described in an earlier paper (Levy and Moxim, 1989). SOURCE is held constant throughout the year with area emissions, principally autos and trucks, released at the surface, and point sources, principally power plants, apportioned as a function of stack height, between the bottom two levels in the model (80m, 500m). Those emissions, which are not deposited in the source regions, become the effective source of NOy available for longrange transport. Since our model has no chemistry to determine the wet and dry deposition of individual nitrogen compounds, the effective source is not calculated explicitly. Instead, it is specified by basing the NOy removal coefficients, cj> and D, on the observed wet deposition of nitrogen and surface concentrations of individual nitrogen species in the U.S. and C a n a d a . The wet deposition coefficient, , is height dependent, proportional to the local rate of precipitation and scaled by a linear parameter (N = 9) t h a t is adjusted to bring the model's yearly integral of wet deposition over North America into agreement with observation (Levy and Moxim, 1987). This value of N also gives a good simulation of the yearly wet deposition of nitrogen over the European source region (Levy and Moxim, 1989). The dry deposition coefficient, D, (Levy and Moxim, 1987; Levy and Moxim, 1989; Levy et al., 1985) uses effective deposition velocities selected in early studies of combustion nitrogen, Weff = 0.3 cm s e c - 1 over land and 0.1 cm s e c - 1 over the ocean. The ocean value is based on observed NOy partitioning over the continent and may underestimate dry deposition of aged NOy. However, increasing W eff over the ocean by a factor of 5 to 0.5 cm s e c - 1 only decreases t r a n s p o r t over the ocean by 20%. Therefore, the neglect of NOy aging should not significantly affect our simulation of longrange transport. While this parameterized treatment of NOy deposition neglects the explicit transport of insoluble species, such as PAN and other organic nitrates, the model's simulation of NOy surface concentrations over the ocean are in reasonable agreement with observations (Levy and Moxim,
Global Deposition
5
1989). The controlling factor is the model's simulation of the meteorology t h a t drives the long-range transport, not the detailed chemistry in the source region and along the transport path. The transport model is integrated for 15 months for each source scenario with the last 12 months used for this study. MODEL EVALUATION The wet removal parameter (N = 9) and the calculated values for W eff , 0.3 cm s e c - 1 over land and 0.1 cm s e c - 1 over the ocean, are based on observations in North America. To check their global applicability, the observed yearly wet deposition over Europe of 1.6 Tg N / y r (Schaug et al., 1987) is compared with the model's self-determined value of 1.4 Tg N / y r . A detailed comparison for a number of representative stations is provided in an earlier paper by Levy and Moxim (1989). The agreement is generally within 2 5 % and seldom worse than a factor of 2. The largest disagreements occur in regions with sharp topographical gradients t h a t produce precipitation features not resolved by the model. While the model's removal parameterization may underestimate wet deposition in Europe by up to 15%-20 + r' i+1
(3
)
Equations (1) - (3) are subject to the following constraints = =
W
and < / ; / ; > = = of where = 0 We a t t e m p t to satisfy these requirements by choosing a random function, p, such t h a t the rain intensity on the i + l s t step is n+l = xr ; + p-1+l
(5)
Taking the mean of (5) we have
= (l-x)
(6)
Using (1) and (3) to substitute for r; +1 and r; in (5) and taking variances results in
2 = (1-xV? + (l-x) 2 2
(7)
We generate rain intensities from equation (5) after choosing a random variate from the lognormal distribution p-l+\ having first and second moments given by (6) and (7). W r ashout Model Once the precipitation intensity is specified according to the model described above, we must calculate the corresponding loss frequency for soluble species. The major assumptions underlying this calculation are the applicability of the semiempirical Frossling equation (Hales, 1972) to estimating the gas phase transport coefficient and use of the Best drop size distribution (Best, 1950). The method, along with other assumptions involved, is discussed in Stewart et al. (1983) and will be briefly summarized here. The soluble species loss coefficient (or loss frequency) is given by
X = -3kW/r
(8)
R.W. Stewart et al.
14
where W is the volume fraction of water in the atmosphere, r is the predominant drop radius, and k is the gas phase transport coefficient. The volume fraction of water during precipitation and the predominant drop radius are related to intensity through empirical power law formulae W =
ClI
C2
and
r = c3IC4
(9)
for the Best distribution where cj = 6.7 x 1 0 - 8 , c2 = 0.846, c 3 = 0.5, c 4 = 0.232 and I is the precipitation intensity in m m / h r . The gas phase t r a n s p o r t coefficient is estimated from the semiempirical Frossling equation. Sh = 2 + O.ôRe^Sc 1 / 3
(10)
where Sh, Re, and Sc are the Sherwood, Reynolds, and Schmidt numbers given by Sh = 2kr/D Re = 2rV z /z/ (n) Sc = i//D where D is the diffusivity of HNO3 in air, v is the kinematic viscosity of air, and V z is the terminal fall velocity for the predominant drop size. For D and v the values used are 0.136 cm 2 sec _ 1 and 0.133 c m 2 s e c - 1 as cited by Durham et al., (1981). The terminal fall velocity is calculated from a formula given by Markowitz (1976) V z - 958(1 - exp((-r/0.885) L 1 4 7 )]
^
Equations (10) through (14) are used to compute the loss frequency, X, as a function of the rain intensity, I. Photochemical model The equations for generating randomly distributed rain periods with random intensity distributions described above have been incorporated into both the one dimensional model of Thompson & Cicerone (1982) and the box model of Stewart et al., (1983). Both models have been applied to selected precipitation scenarios to ensure t h a t the results are substantially modelindependent. The statistics entered into the model prior to a simulation are the mean durations of wet and dry periods, the mean rain intensity during a wet event, the standard deviation of the intensity, and its correlation time. The models are then run for 500 simulated days having equal night and day durations. Precipitation events and soluble species loss rates are generated randomly during these simulations as described above. The simulation period is always sufficient to include at least 100 precipitation events. The statistics necessary to compute the effective loss rate are defined by Xe - < X c > / < c >
(13)
(Stewart, 1988) where Xe is the effective loss, X the actual loss rate, and c the scavenged species concentration, are accumulated during the model
Nitric Acid Removal
Rates
15
simulation. The residence time is then
RESULTS AND DISCUSSION Using the models described above, we have computed the mean H N 0 3 residence time for mean precipitation periods of 24, 48, 84.5 and 96 hours and for wet ratios ranging from 0.05 to 0.30 for each selected period. The mean period is the sum of the mean wet and mean dry periods specified for a model simulation; the wet ratio is the mean wet divided by the mean total period. These assumptions cover the statistical range reported by Thorp (1986) and by Sperber & Hameed (1986) for locations in the Northeastern United States. We have compared the numerical results of each model simulation with the theoretical results of Rodhe & Grandell (1972) and Giorgi & Chameides (1985) calculated for corresponding values of the mean wet ratio, period, and scavenging rate. Giorgi & Chameides considered a range of effective scavenging rate models based on different assumptions regarding the rate of nitric acid recovery following precipitation. The comparison we make is with their instantaneous recovery model in which nitric acid immediately recovers to its pre-precipitation value following a rain event. This model is closer to our numerical results than models which assume slower dry period recovery. TABLE Period (hrs)
w
T(hrs)
Hdays)
%d(RG)
%d(GC)
96
0.051 0.093 0.281 0.342
99.1 99.8 99.9 88.9
5.3 4.2 2.4 1.8
3.3 3.6 1.8 5.2
-16.4 -7.3 27.7 43.3
84.5
0.059 0.103 0.182 0.304
76.2 78.1 84.6 81.5
4.0 3.8 2.8 1.9
7.1 3.2 2.5 3.7
-13.4 -8.8 7.6 31.7
48
0.052 0.106 0.205 0.310
54.1 48.5 47.5 51.0
3.7 2.5 1.7 1.5
-1.8 -5.1 -0.9 -12.0
-21.1 -19.5 -0.9 5.8
24
0.050 0.107 0.191 0.277
28.4 25.5 24.4 25.5
2.9 1.7 1.2 0.9
-3.2 -2.1 -5.1 -6.9
-18.6 -18.2 -14.7 -5.4
The table summarizes the results of the numerical calculations and their comparison for each of 12 scenarios with the Rodhe-Grandell and GiorgiChameides models. The first column is the mean period specified for each model run, w and T in columns two and three are the mean wet ratio and period produced by the model, r i s the nitric acid residence time and the last two columns give the percent difference between the numerical value, r, and
R.W. Stewart et al.
16
H N 0 3 96.0 HR. PERIOD
Q
0.4
HNO3 24.0 HR. PERIOD
0.2
WET RATIO
Figure 2 Comparison of numerical and theoretical HN0 3 residence times. Residence times are shown for mean periods of (A) 96 hrs. and (B) 24 hrs. for various assumed wet ratios. The computed points are connected by a solid (numerical model), dashed (Rodhe-Grandell model), or dotted (GiorgiChameides model) line.
Nitric Acid Removal
Rates
17
the Rodhe-Grandell and Giorgi-Chameides residence time values. The equations used in evaluating the Rodhe-Grandell and Giorgi-Chameides scavenging rates are XRG = X 0 /(l + d 2 TX 0 )
(15)
XQC = (1/QT)(1 - e x p ( - \ 0 T ) )
0.5, hatched areas i t > 0.4 and void areas i t > 0.3. The dashed line indicates the level of the gauge orifice.
Wind Field
Deformation
69
'V
/ I I I I I I
20 %
10%
30 %
F i g u r e 3 Comparison of contour lines of equal percentage increment of wind speed above the Mk2 precipitation gauge. Dashed lines are according to Robinson and Rodda (1969), and solid lines are according to the results of this study. Wind speed is 3 m s - . The figure shows t h a t in the group of P C s having the same orifice area of 200 cm 2 (I-IV) the average increment U m a x decreases with decreasing size of orifice rim. The greatest U m a x value was always observed for ASTA* which had a bird protection ring, and the smallest value for Tretyakov. In the group of gauges having different_magnitudes of orifice area, the abovementioned tendency of decreasing U m a x values with decreasing size of orifice rim seems to be intensified by the increasing orifice area. This is best demonstrated by the Tretyakov and Mk2 gauges. The latter had a greater orifice rim and a smaller orifice area, and thus had greater windward U m a x values than the former. Nevertheless, in the PG group with different magnitudes of orifice area the U m a x values were again related to their ranking as shown in Table 1, particularly for profiles obtained windward and above the center of the orifice. All in all, the range of U m a x values above the orifice center of the seven investigated PG types was from 32% to 46%, indicating the dependency of wind field deformation on the size of orifice rim and orifice area. With regard to the intensity of turbulence, i t , the clear tendency demonstrated above quickly disappears. The value of i t was expressed by the coefficient of variation of wind speed in each measuring point of the profile during the measuring interval of 60 s. During this interval 4000 measurements of wind speed were made. As seen from the distribution of i t in Figure 2, there are two cells in which the turbulence concentrated: inside the PG orifice near the windward and leeward rims. They dominate mainly the range of small wind speeds, and their extent diminishes quickly in the case of wind speed of 7 m s " . Generally, the maximum i t values were observed inside the P G . The gauges with the smallest size orifice rim and
70
Boris Sevruk et al.
the largest orifice area (China and Wild), show the largest i t values. Mk2 and ASTA* show the smallest i t values. Considerable differences between the PG types are evident if the positions of maximum i t values are considered. The large values of i t leeward of the Hellmann PG orifice are interesting. They may be due to the specific form of the rim of this gauge which hangs inside over the orifice, like a console. However, the role of intensity of turbulence with regard to the deficit of PG catch is not yet clear. The results of this study are in line with the results of other authors (Robinson and Rodda, 1969), as shown in Figure 3. The contour lines of equal increment of wind speed above the Mk2 gauge orifice agree well. REFERENCES Robinson, A.C. & Rodda, J.C. (1969) Wind and the aerodynamic characteristics of rain-gauges. Met. Mag. 98 (1161), 113-120. Sevruk, B., Hertig, J.-A. & Spiess, R. (1988) The effect of precipitation gauge orifice rim on the wind field deformation as investigated in a wind tunnel. In: Proc. J^th International Workshop on Wind and Water Tunnel Modelling of Atmospheric Flow and Dispersion. Karlsruhe, GFR, 3-5 Oct. 1988 (Preprint).
Atmospheric Deposition (Proceedings of the Baltimore Symposium, May 1989). IAHS Publ. No. 179.
M O N I T O R I N G A T M O S P H E R I C D E P O S I T I O N IN CALIFORNIA'S SIERRA NEVADA: A COMPARISON OF METHODS Bruce J. McGurk Hydrologist, Pacific Southwest Forest and Range Experiment Station, Forest Service, P.O. Box 2Jt5, Berkeley, California 94-701, USA
USDA
Neil H . B e r g Hydrologist, Pacific Southwest Forest and Range Experiment Station, Forest Service, P.O. Box 2Jt5, Berkeley, California 94-701, USA
USDA
Danny Marks Assistant Research Hydrologist, Center for Remote Sensing and Environmental Optics, University of California, Santa Barbara, California 93106, USA John M. Melack Professor, Department of Biological Sciences, University Barbara, California 93106, USA Frank Setaro Marine Science Institute, 93106, USA
University
of California,
of California,
Santa Barbara,
Santa
California
ABSTRACT Four methods for measuring atmospheric deposition in the Sierra Nevada of California were compared during the winter of 1986-1987. A large (28 by 122-cm) polyvinyl chloride tube was compared to a Belfort precipitation gauge and to snowboards at both an exposed site, near Mammoth Lakes, and a site in a forest clearing, near Soda Springs. An Aerochem Metrics collector was also included at the forest site. At the exposed site, the tube and the Belfort gauge caught 23% less snow water equivalent than the snowboards. In the clearing, the tube and the Belfort gauge caught 17% more than the snowboards. Except for N 0 3 at the forest site, chemical analyses of samples from the tube and the snowboard showed t h a t H, N 0 3 , and S 0 4 concentrations differed significantly (p < 0.05). Laboratory tests showed no adsorption or desorption of synthetic s t a n d a r d solutions of major ions from the tube. For sheltered sites with occasional midwinter rain, the tube is recommended. For windy sites without midwinter rain, sampling from weekly snowboards provides a better estimate of chemical and snow volume loading. INTRODUCTION Stations t h a t monitor atmospheric deposition must obtain both elemental concentrations and precipitation volume to estimate total chemical loading. Snowfall in the Sierra Nevada of California has relatively low concentrations of chemical constituents compared to rain or to precipitation elsewhere in the USA (Feth et al. 1964, Melack et al. 1982, Woo & Berg 1986). However, because a meter or more of water falls as snow compared to a few centimeters of rain per year in the Sierra, accurate measurement of both volume and chemical concentration of the snow is crucial. Between 71
72
Bruce McGurk et al.
1984 and 1987, in the central Sierra Nevada, the mean annual chemical loading from snow was 3.8 times t h a t of rain (Marks et al. 1988). Snow accumulation is difficult to measure accurately because of the influence of wind on low-density snow crystals. Snowfall rates and volumes are the least accurate component of hydrological modeling (Peck 1972), and these difficulties are compounded in mountainous environments where winds are high and terrain is rugged. It is difficult to maintain a gauge at a fixed height above the snow surface and to design a collector t h a t is sensitive to but not overwhelmed by single storms t h a t can deposit more than 75 cm of snow. Few studies have evaluated the undermeasurement by Belfort-type gauges by comparing their catches to measurements of snow on the ground or on snowboards (Goodison 1978, McGurk 1986). Extensive efforts have been made to design and test wind screens or shields to prevent entrainment of snow crystals and the resultant undercatch (Larson & Peck 1974, Goodison et al. 1981). Gauges equipped with shields catch more precipitation than unshielded gauges, but catch efficiency decreases as wind speed increases to 10 m s . A serious undercatch is suspected above 10 m s~ . Because stands of trees reduce wind speeds, forest clearings are preferred for precipitation gauges. Many mountainous areas, however, have little forest cover and have high wind speeds; therefore collection networks may require a range of techniques to obtain accurate information at alpine sites. Also, some areas of the Sierra Nevada receive midwinter rain, so the characteristics of the site may affect the choice between snowboards or tubes. STUDY DESIGN AND METHODS Our study was designed to evaluate a polyvinyl chloride (PVC) tubular collector (Dawson 1986) and to determine if it would collect accurate samples of volume and yield water suitable for chemical analysis. Snow volumes were also measured by high-capacity Belfort weighing-precipitation gauges and five 0.36-m 2 snowboards. The tubes, Belforts, and two boards were measured once per week. A set of three boards was measured once a day if precipitation occurred. Made of Schedule 80 (0.5-cm walls) irrigation pipe, the PVC tubes were 122 cm long and 28 cm in diameter. A cap was glued on one end, and the other end was beveled. The tubes were acid-washed and repeatedly rinsed (AWRR) with deionized water before installation. The tubes and Belfort gauges were equipped with Alter wind screens placed at orifice height. Rinsed tubes were replaced weekly, and tubes with precipitation were allowed to melt indoors at 15 ° C. Meltwater volume and pH were measured at the field site laboratories. The remainder of the sample was refrozen in AWRR linear polyethylene bottles for transport to the Santa Barbara laboratory. Liquid volume was converted to weekly areal depth for comparison with the other measurement techniques. Both the weekly and the 24-h event snowboards were measured at about 0800 h on the weekly change date or after any 24-h interval with precipitation. Depth was measured at all four corners of the board and a 10-cm diameter PVC tube was used to cut cores t h a t were weighed on a top-loading balance. Replicate snow samples were collected with an AWRR 4-cm polyethylene tube. The depth-integrated sample was placed in AWRR 2-liter polyethylene bottles. At the sheltered site, weekly samples were collected from an Aerochem Metrics collector. Field chemistry and volume measurements were made as described for the 24-h boards. This sampler is also used in both the California Acid Deposition Monitoring Program (CADMP) and the National Acid Deposition Program (NADP).
Monitoring Atmospheric
Deposition
73
At the Santa Barbara laboratory, the major cations (calcium, magnesium, sodium, and potassium) were analyzed with a Varian-AA6 atomic absorption spectrophotometer. An air-acetylene flame was used; addition of l a n t h a n u m chloride suppressed chemical and ionization interferences during calcium and magnesium determinations. The organic anions (acetate and formate) and inorganic anions (chloride, nitrate, and sulfate) were measured with a Dionex Model 20101 ion chromatograph employing chemical ion suppression and conductivity detection. Measurement of pH was made with a Ross 8104 combination pH electrode on a Fisher Acumet 805 MP pH meter. Before each trial, the electrode was calibrated with pH 7.00 and pH 4.00 buffers. After thorough rinsing with deionized water, a calibration with a freshly prepared 10~ 4 M HC1 solution was performed. S T U D Y SITES Two sites, the Central Sierra Snow Laboratory (CSSL) and Mammoth Mountain, were selected as representative of portions of the Sierra Nevada where snow is important (Figure 1). CSSL is 1 km east of Soda Springs, California (39 ° 19 26" N, 120 ° 22 W), and is in the mixed conifer-fir zone. The Belfort gauges and the tubes were on two 8-m towers in a 40 x 50 m clearing at 2100 m a.m.s.l. An Aerochem Metrics sampler was on a 7-m tower. Mean annual precipitation is 139 cm (California Cooperative Snow Survey 1987), of which 120 cm is snow. The peak depth is about 3 m of snow t h a t is isothermal near 0 ° C and has a dilute chemical load (Berg 1986). Surface wind speeds are low, and midwinter melt and rain occur. Forest cover may be locally dense but with numerous openings. Much of the central Sierra Nevada has a similar forest cover. The open study site was located at Mammoth Mountain Ski Area (37 ° 28' 16" N, 119° 01 38" W) at 2940 m a.m.s.l, about 3 km west of Mammoth Lakes. Mean annual precipitation is 142 cm (California Cooperative Snow Survey 1987), and a 3 to 4-m accumulation of snow is common. All instruments were mounted on a 6-m platform. This site is similar to much of the alpine zone of the central and southern Sierra Nevada and has high winds and no midwinter rain. QUALITY CONTROL A N D QUALITY ASSURANCE The study design included a program to ensure accuracy and comparability between sites for both volume and chemistry measurements. Identical instruments were used, and adherence to standardized d a t a collection procedures and field analysis protocols was emphasized with the field staff at both sites. Replication of volume measurements and sample collections allowed estimation of procedural variability and of confidence intervals around mean values. Precipitation volume All Belfort gauges were calibrated across their full range both at the s t a r t and t h e end of the season. Snowboards, snow density cutters and tubes, and other equipment for both sites were fabricated and calibrated by the manufacturer or our technicians. Precipitation chemistry All containers and washing procedures were assessed for adsorption and desorption of major ions and for post-washing chemical contamination, respectively. No adsorption or desorption was detected after addition of
74
Bruce McGurk et al.
F i g u r e 1 Location map of snow study sites, Central Laboratory and Mammoth Mountain, California.
Sierra
Snow
known synthetic standards. Contaminants were below detection limits, in 9 1 % of 98 ion samples from PVC cylinders, polyethylene bags, and polyethylene bottles after AWRR. Performance at the field sites was assessed by means of field blanks and field audit samples. The blanks were final rinses from the tubes and other samplers which were placed in AWRR bottles and sent to Santa Barbara along with a sample of the deionized water used t h a t day. Audits were for pH or conductivity and were sent to the field sites from Santa Barbara. At Santa Barbara, freshly prepared calibration s t a n d a r d s t h a t bracketed the samples' concentrations and reagent blanks were used in every assay. Charge balance controls were included in each analytical run to determine if a persistent deviation in anions and cations existed. Accuracy was assessed by comparison with certified controls, and precision was estimated by analyzing 5% of the samples in a run in duplicate. PRECIPITATION VOLUME RESULTS Although only 60% of the mean precipitation was deposited in water year 1987, precipitation was recorded during 15 weeks of the 16-week monitoring period. During only 5 weeks at Mammoth and 6 weeks at CSSL did precipitation SWE exceed 4 cm (Figure 2). Also, during 5 weeks at Mammoth and 6 weeks at CSSL, minor amounts of precipitation were detected in the tubes but not on the snowboards. At Mammoth, the towermounted collectors caught significantly less snow water equivalent (SWE) than did the snowboards during both large storms and for the seasonal total (Table 1). The 5-month mean wind speed was 3.3 m s - 1 at Mammoth versus 1.3 m s - 1 at CSSL; this difference may explain the approximate 2 3 % seasonal undercatch by the Belfort and the tube at Mammoth. This undermeasurement is approximately what Larson 8i Peck (1974) predicted
Monitoring Atmospheric Deposition
12/23
1/06
1/27
2/03
2/17
2/24
3/10
3/17
3/24
4/08
75
4/24
Week Ending (Date) in Water Year 1987
12/23 1/06
1/20
1/27
2/03
2/10
2/17
2/24
3/10
3/17
3/24
3/31
Week Ending (Date) in Water Year 1987
Figure 2 Mean weekly precipitation (> 0.5 cm water equivalent) measured by several methods during the 1987 winter at the Central Sierra Snow Laboratory (A) and Mammoth Mountain (B), California. for a shielded gauge collecting snow. At CSSL, the tower-mounted collectors caught significantly more SWE than the snowboards (p < 0.01). The 10.5-cm difference is about halved once the 4.3 cm of rain that occurred during two storms is added to the
Bruce McGurk et al.
76
T a b l e 1 Mean precipitation depths between 17 December 1986 and 8 April 1987 at two sites in the Sierra Nevada, California Site
Central Sierra Snow Laboratory Mammoth Mountain
Belfort gauge
PVC tube
24-h board
Weekly board
70.8
73.4
62. T1
61.12/
42.9
48.6
57.5
60.9
Aerochem Metrics 50.8
-
1 / Aerochem Metrics sampler a t CSSL was not replicated. 2 / Underestimated due to rain.
board depths. Rain during the weeks of 17 February, 10 March, and both April weeks contributed to the comparatively low weekly and 24-h board SWE depths (Figure 2). Analysis of variance on the weekly results from the Belfort and tube yielded no significant differences at either site. At CSSL, the 24-h and weekly boards were also not significantly different. The other combinations of Belfort, tube, and boards had significantly different weekly volumes (p < 0.01). Analysis of the replicates showed t h a t the 95% confidence intervals (CI) around the mean weekly differences for the Belforts, tubes, and weekly and 24-h event boards averaged +0.4 cm and ranged from +0.2 cm to +0.6 — cm. ~~ The Belfort gauges and the tubes caught 42% more precipitation at CSSL than did the Aerochem Metrics sampler (Table 1). The wind screen cannot be fitted to this sampler, and the screen's absence may account for p a r t of this difference. An Aerochem Metrics was used for several years at the windy Mammoth site with little success (Dawson 1986). At CSSL, considerable maintenance is required to free the collector's movable arm when it freezes in place and to empty the shallow (40 cm) buckets during large snow storms. PRECIPITATION CHEMISTRY RESULTS For the PVC tube and weekly boards, analysis of variance for H, S 0 4 , and NO3 identified significant differences (p < 0.05) in concentration between the three constituents except for N 0 3 at CSSL. At both sites, mean concentrations of the replicates for all three constituents were generally greater in tube samples than in weekly board samples. Except for Ft, 9 5 % CI around the difference between the replicates for each constituent at CSSL were much greater (2- to 30-fold) for the tube samples t h a n for the weekly board samples. At CSSL, CI for the weekly boards varied from +0.3 //eq L _ 1 for S 0 4 to +2.4 //eq L - 1 for CI and from +1.1 //eq L - 1 for FT to + 13.7 //eq L" 1 for C l i n the tube. At Mammoth, the"95% CI for the boards and tubes were more similar. For the weekly boards, CI ranged from +0.4 //eq L~ ! for K to +5.5 //eq L _ 1 for Ca and from +0.5 //.eq L~ ! for H to +~2.8 //eq L " 1 for CI in fïïe tube. Variability was greatest for CI, Ca, and Na.~"" Both the concentrations of H, S 0 4 , and N 0 3 .and the snow volumes were generally greater from the tube samples at CSSL than from the weekly boards samples (Figures 2A and 3A). The boards caught snow and the tube
Monitoring Atmospheric Deposition
Tube (neq/L)
Figure 3 Selected chemical concentrations at the Central Sierra Sno Laboratory (A) and Mammoth Mountain (B) as measured by PVC tuband weekly snowboards during 1986-87.
77
78
Bruce McGurk et al.
did not during 2 weeks, and the reverse situation occurred during 6 weeks. The cumulative loading in the tubes during these 6 weeks was appreciable due to relatively high chemical concentrations. Therefore, the seasonal loading of 28.0 meq m - 2 at CSSL, estimated from the tube concentrations and SWES, greatly exceeded the loading of 15.1 meq m - 2 estimated from the weekly board concentrations and SWES. Samples from the tubes had generally higher concentrations than samples from the weekly board at Mammoth (Figure 3B). However, because 25% less snow was caught in the tubes at Mammoth than on the boards (Table 1, Figure 2B), the tube's seasonal loading of 13.0 meq m~~2 was only slightly higher than the 12.1 meq m^ 2 estimated from the boards. Although the tubes captured snow during 5 weeks when the boards did not, the volume was small and, unlike CSSL, the concentration was similar to t h a t found on the boards. At CSSL, the loading estimate from the Aerochem Metrics sampler was 17.5 meq m~~--16% more than the board's loading and 37% less t h a n the tube's loading. Because the Aerochem also caught 28% less SWE than the tube, the volume-corrected loading would be close to the tube value. Because the sampler excludes dry deposition from the precipitation bucket, the larger loadings t h a t result from the use of plastic collectors vs^ boards are probably not related to dry deposition. This study could not determine whether rain, surface melt, or sublimation reduced the board loading. CONCLUSIONS Although the chemical concentration in snow is low compared to t h a t in rain in the Sierra Nevada, the seasonal loading from snow compared to t h a t from rain mandates the monitoring of snow in the Sierra Nevada. The SWE from the shielded Belforts and PVC tubes was the same at both sites, and the weekly depths and the sum of the daily board depths were the same at CSSL. Significant differences were found among the other combinations of the Belfort, tube, and board SWEs. At moderate elevations in the Sierra Nevada, where forest cover exists and rain occurs, we recommend the shielded PVC tube for weekly monitoring of SWE and chemical concentration. In the higher areas of the Sierra Nevada where rain does not occur and forest cover is less common, we recommend sampling by weekly snowboards. They have the added advantage over tubes of not needing a tower, a windscreen, and weekly rinsing with deionized water. A disadvantage of the boards is the laborintensive, detailed procedures t h a t must be followed to obtain accurate depth and density measurements and uncontaminated samples for chemical analysis. The tube did not adsorb or desorb ions during tests with synthetic solutions. However, the comparison of weekly samples showed t h a t the PVC tubes had significantly higher concentrations of most ions than did the snowboards. The reason for this difference is not known, but is worth more research because of its implications in network design. The Aerochem Metrics sampler used in the CADMP and NADP networks is not suitable for snow collection because of its undermeasurement problems, mechanical malfunctions, and small bucket capacity. A C K N O W L E D G E M E N T S We t h a n k Dan Dawson, Dan Whitmore, Jim Bergman, Joe Lipka, Jeff Cook, and Randall Osterhuber for collecting d a t a . Dr. Kathy Tonnessen provided design and operational assistance and manuscript review. The staff at Mammoth Mountain Ski Area provided the instrument tower and area access. The study was funded by the California Air Resources Board Grant A6-078-32, as amended.
Monitoring Atmospheric
Deposition
79
REFERENCES Berg, M.H. (1986) Snow chemistry in the central Sierra Nevada, California. Water, Air, and Soil Pollution. 30, 1015-1021. California Cooperative Snow Survey (1987) Water Conditions Fall Report, Dept. W a t . Resour., Sacramento, CA.
in
California,
Dawson, D.R. (1986) Acid deposition monitoring in an alpine snowpack. Final Report, California Air Resources Board, Contract, A4-038-32. Marine Science Inst., Univ. of California, Santa Barbara, CA, USA. Feth, J.H., Rogers, S.M., & Roberson, G.E. (1964) Chemical composition of snow in the northern Sierra Nevada and other areas. Water Supply Paper 1535J. Washington, US Dept. Interior Geological Survey. Goodison, B.E. (1978) Accuracy of Canadian snow gage measurements. Appl. Met. 27, 1542-1548.
/.
Goodison, B.E., Ferguson, H.L., & McKay, G.A. (1981) Measurement and d a t a analysis. In: Handbook of Snow (ed. by Gray, D.M., and D.H. Male), 191-274, Pergamon Press, Toronto. Larson, L.W., & Peck, E.L. (1974) Accuracy of precipitation measurements for hydrologie modeling. Wat. Resour. Res. 10(4), 857-863. Marks, D., McGurk, B., & Berg, N. (1988) Snow volume comparisons for atmospheric deposition monitoring. Proc, Western Snow Conf., 56, 124-135. McGurk, B.J. (1986) Precipitation and snow water equivalent sensors: an evaluation. Proc. Western Snow Conf. 54, 71-80. Melack, J.M., Stoddard, J.L., & Dawson, D.R. (1982) Acid precipitation and buffer capacity of lakes in the Sierra Nevada, California. In: International Symposium on Hydrorneteorology (ed. by A.I. Johnson & R.A. Clark), 465-472, Am. W a t . Resour. Assoc, Denver. Peck, E.L. (1972) Snow measurement predicament. 244-248.
Wat. Resour.
Res.
8,
Woo, S., & Berg, N.H. (1986) Factors influencing the quality of snow precipitation and snow throughfall at a Sierra Nevada site. Proc. Cold Region Hydrology Symposium., 201-209, Am. W a t . Resour. A s s o c , Anchorage, AL, USA.
