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Comparison of surrogate surface techniques for estimation of sulfate dry deposition
Atmospheric Environment Printed
in Gnat
Vol. 19, No. 4, pp. 627435,
@X4-5981/85
1985 0
Britain.
$3.00 + 0.00
1985 Pergamon
Press Ltd.
COMPARISON OF SURROGATE SURFACE TECHNIQUES FOR ESTIMATION OF SULFATE DRY DEPOSITION* JOHNJ.VANDENBERG~~~
KENNETH
R.KNOERR
School of Forestry and Environmental Studies, Duke University, Durham, NC 27706, U.S.A. (First received 14 October 1983 and
infinalform
23 July 1984)
Abstract-The dry deposition rates of sulfate particles to artificial surfaces within and above a mature hardwood forest were measured over an annual range of synoptic weather conditions. Artificial, or ‘surrogate’, surfaces representing both rough and smooth textural types included deposition buckets, petri dishes, filter paper, Teflon configurations and polycarbonate membranes. Ambient concentrations of sulfate and sulfur dioxide were also monitored. The artificial surfaces were evaluated on the basis of the magnitude of the sulfate dry deposition rates and measurement precision. Correlations between techniques and the magnitude of the deposition velocities identified technique similarities. Ambient concentrations of the sulfur oxides and the deposition rates were not well correlated. For diverse reasons, many of the techniques were found to have limited reliability. The petri dish, bucket inside and filter plate surfaces were found to represent the most precise devices for the estimation of dry deposition to smooth, complex and rough artificial surfaces, respectively. Seasonal averages for samplers exposed at all heights were 11.2, 27.7 and 71.2 pg SO:- mm2 h- ‘, yielding mean deposition velocities to surfaces exposed within the forest canopy of 0.03,O.11 and 0.14cm s- ’ and an annual estimate of the potential dry deposition to a foliated hardwood forest of 4.0, 11.5 and 21.0 kgSO:- ha-’ for the petri dish, bucket inside and filter plate surfaces, respectively. The indirect ratio between deposition rates and velocities results from varying concentrations of ambient sulfate between sampling periods. The accuracy of the filter plate data is suspect due to a significant correlation with sulfur dioxide concentrations. Sulfur concentration and deposition rate gradients indicate the forest is providing a net sink for sulfur pollutants during periods with foliage. The wide range of dry deposition rates estimated from the variety of deposition surfaces emphasizes the uncertainty of the artificial surface measurement techniques. In spite of these limitations, surrogate surfaces provide an estimate of sulfate flux rates not currently obtainable from natural surfaces. Key
word
index: Dry deposition, sulfate, air pollution, forest.
restricted use due to stringent site requirements, expense and sampling problems (Garland, 1974; Droppo, 1979). Dry deposition has also been estimated on the basis
INTRODUCTION Vegetation pollutants deposition
may provide an important sink for air through the absorption of gases and the of substances in rainfall and dryfall. When
of ‘surrogate’ collecting surfaces. Surrogate collectors are potentially useful in that they provide a common surface available for application in a variety of environments which avoid the problems of uptake or leaching from plant parts. Surrogate surfaces which have been used in dry deposition studies include sampling devices such as open buckets, petri dishes, Teflon, coated and uncoated glass, filter paper, plastic nets and artificial foliage (Hicks et al., 1980; Eisenbud and Harley, 1955; Nihlgard, 1970; Heesen et al., 1979; Schlesinger and Reiners, 1974). For each of these surrogates, the processes acting to deposit material may be affected by the particle attraction and capture characteristics of its surface and by the local turbulence induced by its size and Shape (Munn and Bolin, 1971). Differences in size and shape, and therefore in the rate of dry deposition, among various surrogate surfaces and natural surfaces have severely limited the extrapolation of data from one surface type to another (Hosker and Lindberg, 1982; Droppo, 1974). While previous work has shown that dry deposition to both surrogate and natural surfaces is directly related to
attempts have been made to estimate dry deposition via leaf washing techniques, they have proven to be of limited value for pollutants such as sulfate and nitrate. These compounds are plant nutrients, which can move across the cuticle of plant leaf tissues. In these estimates there is considerable uncertainty about what portion is dry deposition and what portion has been derived from an internal plant pool (Attiwill, 1966; McCall and Bush, 1978; Lindberg et al., 1979). As an alternative, some field measurements have used meteorological methods to estimate the mass transfer of pollutants to plant canopies. Of these approaches, the gradient and eddy-correlation techniques show promise in estimating total mass flux from the atmosphere to a forest canopy (Everett et al., 1979; Hicks et
al.,
1982). However,
these techniques
have
*This study was a cooperative effort of the Duke University School of Forestry and Environmental Studies, the Aerosol Research Branch of the U.S. Environmental Protection Agency, and the Research Triangle Institute. 627
628
JOHN J. VANDENBERG and KENNETH R. KN~ERK
wind velocity under wind tunnel conditions (Little, 1977) little information is available from the more complex conditions in field experiments. The present study evaluates the dry deposition ot sulfate to a variety of surrogate surfaces, and provides a basis for comparison of these surfaces. The surrogate sampling surfaces were deptoyed within and above a mature deciduous forest to evaluate dry deposition at different canopy levets. Sulfate dry deposition velocities to the surrogate surfaces,and net canopy removal of particulate sulfate were calculated. Samples were collected periodically from January 1981 to April 1982, to evaluate the effects of seasonal changes in vegetation and weather conditions. METHODS
The research site was located in the Blackwood Division of the Duke Forest, situated in the gently rolling central Piedmont of North Carolina, about 16 km west of Durham, The surrogate sampling devices were depioyed on a 40-m meteorologicaf tower that extends through and above a 25- to 28-m mixed deciduous forest. The dominant tree species include white oak (Quercus &a), hickory (Caryu spp.) and tulip poplar (Liriodendron tutiperi$em) in the overstory and dogwood (Cornusjforida) in the understory. Sample collection and analysis
Replicatepairs of surrogate surfaceswere deployed at each of the four sampling levels within and above the forest canopy. The sampling levels were at heights of 1, 12, 25 and 36m above the forest floor, corresponding with the forest floor region, the region between overstory and understory canopies, the area of overstory canopy closure, and above the forest foliage, respectively. Surrogate surfaces representing both rough and smooth textural types included 28.6sm diameter ~lyethylene deposition buckets, 9cm diameter polystyrene petri dishes with and without Whatman 41 cellulose filters taped inside, 9-cm wide by 27-cm long Teflon sheets in both solid bar form and as Teflon sheets affixed to a stainless steel core, 4.7-cm diameter Nuclepore No. 111105 polycarbonate membranes held in circular filter holders, and a sheet of Pallflex E70207SW cellulose-glass filter paper held within a stainless steel frame to expose a 13.2 x 182cm rectangular portion of filter paper. During surface sampling periods simultaneous measurement of the ambient concentrations of sulfate and sulfur dioxide were monitored at the top and bottom of the tower with U.S. EPA high-volume samplers and Huey sulfation plates, respectively. For periods when on-site, highvolume samples were not available, ambient sulfate concentrations were measured by the Research Triangle Institute (RTI), Research Triangle Park, N.C., some 22 km away. Comparison of simultaneous high-volume measurements made at the Duke Forest and RTI sites demonstrated a strong correlation (r* = 0.93) between the ambient sulfate concentrations at these locations. Prior to deployment on the tower, the bucket and Teflon surfaces were thoroughly washed with deionized water and dried with ethanol. The other surfaces and filters were used directly from the manufacturer, with any frame or material in contact with the collection surfaces cleaned with deionized water and ethanol. During the preparation and extraction of the sampies, all equipment was handled using polyethylene
glovesand cleaned thoroughly to avoid contamination. At the end of each exposure period, the sampiers wereremoved from the tower and returned in a clean carrier box to a field laboratory for extraction. Surface samples were extracted
using known volumes ol’ eluent (0.003 M HCC,. 0.0024 M CO:- 1, and transported in clean polypropylene bottles to the laboratories for analysis. Samples collected during this project were analyzed for sulfate (SO: ) concentrations by the EPA and RTI laboratories using standard ion chromatography techniques. Analysis of system accuracy, based on US. primary standards, indicated an average accuracy for the RTI laboratory of & 2 “, and an average precision of f 3 9, over a wide range of concentrations. The EPA laboratory was not required to process blind primary standards, although a test of system accuracy at the end of the experimental period indicated an accuracy of rf. 15Yo. Statistical analysis for each sampling device mcluded a calculation of univariate statistics on a seasonal basis, with deposition velocities in units of ems-’ calculated for each exposure period by dividing the deposition rate (pgcm ’ s ‘) by the ambient sulfate concentration bgm-“). A correlation coefficient matrix was developed which related each sampling device to every other one. The rate of sulfate deposition to some of the surrogate surfaces was used to estimate pollutant removal by the forest canopy through a caiculation of the total flux rate to a typical multilayered canopy. The total flux rate is equal to the summation of the deposition on upward and downward facing surfaces (taking the leaf area index into account) plus the ground flux, with each component expressed per unit ground area. This analysis assumes that the flux rates to the smooth and rough surrogate surfaces encompass the range of flux rates expected for a leaf surface. Summing upward and downward surfaces within the canopy attempts to simulate the actual deposition on leaves which experience impaction of particles on all surfaces. RESULTS AND DISCUSSION
Initial experiments indicated that for some of the sampling surfaces a dry deposition period of at least two days was necessary to distinguish an a~umu~ation of sulfate above background levels. Thus the sample periods were kept as long as feasible, averaging 86 h (range 24- 143; N = 13). Twenty-nine attempts were made to collect dry deposition. Of these, thirteen were successfully completed without a precipitation event. However, during five of the thirteen periods the local climatological record indicated the potential for nocturnal dew formation (r.h. 2 9Sj10) (NOAA, 1981, 1982). Comparison of the deposition rates during periods with and without potential dew formation did not indicate substantial profile differences. Thus, while dew formation may have enhanced the deposition rates during some periods through aerosol nucleation and coalescence and Stefan flow, the effect was believed to be relatively minor (Hicks, 1983). Two periods with very slight rainfalls of 1.3 and 0.2 mm (6 0.05 in and 4 0.01 in, respectively) were also analyzed to provide examples of sulfate deposition with minor precipitation events. Both of these minor rainfall periods displayed deposition rates at least an order of magnitude greater than typical dry deposition rates, with the smallest rainfall event having the highest flux rate. These results show that even very small amounts of precipitation can contaminate dry deposition sampies. Periods with rainfail events were therefore excluded from further anaiysis.
Solid
- 0.02
0.50
0X2*
0.13
0.33
0.81*
0.73**
0.24
-0.06 -0.27
0.42*
0.06 -0.14
0.82**
0.65*
0.57
0.01 0.34
0.32 0.52
0.15
0.25 0.41
0.43
-0.62 0.37
- 0.47 -0.21
downfacing
Teflon
- 0.23 -0.20
Bucket inside
0.48
0.28
0.10 0.02
0.14 0.52
-0.15 0.31
Solid Teflon upfacing
0.69**
0.53** 0.55
0.36* 0.34
- 0.26 0.33*
Steel Teflon downfacing
.. -
_.
.,.
-. .
.“,
-
-I
,.
-
--
-_
0.65** 0.77**
0.29 0.72**
0.06 0.09
steel Teflon upfacing
*One asterisk indicates significant coefficients at the P G 0.05 level, two asterisks at the P < 0.01 level.
High volume Huey sulfation plate Filter plate Polycarbonate membrane Petri dish Petri dish filter Steel Teflon upfacing Steel Teflon downfacing Solid Teflon upfacing Solid Teflon downfacing Bucket inside
Bucket outside
_-
-,.
0.97**
0.68* 0.81*
0.31 -0.34
Petri dish filter
-..
-0.21 0.58**
0.15 0.00
Petri dish
Table I. Correlation coefficient matrix for sulfate dry deposition to surrogate surfaces
-
,” ._
0.22
0.52 0.18
Polycarbonate membrane
. .._..
0.34 0.65**
Filter piate
_.
._.
0.13
Huey sulfation plate
630 Correlation
JOHN J. VANDENBERG and KENNETH K. KNOERR
coeficients
Correlation coefficients calculated for the dry deposition rate of sulfate to the various surrogate surfaces were generally positive and often significant (Table 1). In general, the significant correlations were found between surfaces with a similar texture or geometry, with the highest correlation coefficients for any device being with that device used in another way. Thus, the smooth, low profile Teflon, petri dish and polycarbonate membrane surfaces were highly correlated with each other. The smooth bucket inside and outside surfaces with their greater profile in each dimension had highest correlations with each other and with the smooth Teflon surfaces. The relatively rough texture and low profile of the filter plate surface showed highest correlation with the similarly textured petri dish filter surface. From this pattern of correlations it may be concluded that the primary factor controlling the dry deposition rate of sulfate to surrogate surfaces is the texture and geometry of the sampling device. There was some redundancy in Teflon deposition surfaces. The use of different construction materials was intended to determine if the dry deposition rate of sulfate to Teflon was significantly affected by electrostatic effects. Mean deposition rates to the solid core and steel core Teflon surfaces were very similar in magnitude, with a t-test of similarly-oriented faces showing no significant differences between the means. Thus, any electrostatic effects related to the construction of the Teflon surfaces did not significantly affect the dry deposition rate of sulfate to Teflon, similar to conclusions of Davidson (1977) and Droppo (1974). One deposition surface, the filter plate, had a highly significant correlation with the ambient concentration of sulfur dioxide. This may reflect the effect of SO2 absorption on the formation of extrinsic sulfate on the cellulose-glass filter paper surface. Axelrod et al. (1971) have reported sulfate artifact formation on alkaline glass fiber reaction sites, with a corrective pretreatment procedure suggested by Forrest and Newman (1973). The filter paper used in the present project was not treated prior to tower deployment, thus the flux rates reported for this surface must be considered suspect and likely indicating the deposition of particulate sulfate with some sulfur dioxide interference. A comparison between the techniques for measuring ambient concentrations of sulfate and sulfur dioxide, i.e. the high-volume sampler and Huey sulfation plate, revealed that the ambient concentrations of sulfate and sulfur dioxide were poorly correlated (r = 0.13). This contrasts with Sandberg et al., (1976) who found a correlation coefficient of 0.70 between the sulfur species. However, Sandberg’s correlation was determined on a mean annual basis, which effectively damped out any direct, day to day variations that were associated with our study. While we expected a correlation between dry deposition and ambient concentration of sulfates, such a
correlation was not found in our experimental data. We feel that this lack of correlation may have at least two causes. The first is that the ambient \ulfate concentrations had only a limited range of values ov’er the series of sampling periods. The second is that we had to expose our sampling devices for a several days period (usually 2~4 days) to obtain measurable quantities of deposited material. During each ot‘ these sampling periods there may have been variation in the ambient concentration of sulfate as well as diurnal variation in atmospheric stability and wind speed which affected the deposition process. When there is variation in both concentration and turbulence processes affecting deposition during a sampling period, the average deposition may be poorly correlated with the average ambient concentration. While not reported we also tested the correlation between deposition and average wind velocity during the sampling periods. This correlation was also insignificant, we believe, for the same reasons that the was with ambient concentration correlation insignificant. Sample variability
Multivariate analysis of variance was used to assess the major sources of data variability. The two scales of spatial variability (i.e. the variability between simultaneously exposed replicate samples and the variability associated with vertical distance from the forest floor) were compared to each other and to the temporal variability. The variability in the deposition rate associated with the vertical position and sampling date factors was usually found to be highly significant and similar in magnitude as demonstrated by the petri dish data in Table 2. The variability associated with these factors was also much larger than the variability associated with the two replicate samples at each level. These results suggest that the analytical and sampling variability provide relatively small contributions to the total observed variability. In addition, with the vertical and temporal variability components generally of the same magnitude, the data set generated in this project may be represented by statistics averaged across space and time. For each sampling technique, results are presented in Table 3 on the mean and median coefficient of variation (CV), sample size, ratio of net measurement to background level and mean dry deposition rate or Table 2. Three way analysis ofvarrance of the petri dish data Contribution to total variation Source of variation
( “,,I
df’
I
Replicate Date Position Date *position
0.2 37.2 1x.9 43.6
1
0.51
9 3 27
5.42* x.22* 7.1 If ___
*Asterisks indicate significant sources of variation at the P < 0.05 level; d.f; degrees of freedom: F, F-value.
-..,-
,,
-
Filter giate Polycarbonate membrane Petri dish Petri dish filter Steel Teflon upfacing Steel Teflon do~nf~ing Solid Teflon upfacing Solid Teflon downfacing Bucket inside Bucket outside High volume sampler Huey sulfation piate
Surface or T~hniqu#
_
_
-
_
.,.
_
,_
_
-
.,,
7.3
-
10.8
f5) (471
12.1
_-
-
f121
(2) 9.0
(8’ 33.3 (12) 23.2 18.0 (12) 4.4 4.4
34.4
35.9 “I) 21.6 (18) 29.0 19.1 S8) 3.0 2.4
42.4
(8)
41.6
41.7
41.6
(11) *
7.0
17.6
6.9
9.0
t2) 2Q.6 s2t 31.5 24.0 (121 31.1 27.7
(10)
(20)
(12)
36.7
48.5
7.0
16.6
22.5 (I’) 15.9 (40) 32.1 23.2 (44) 33.9 28.7
9.5
13.2
3.6
7.0
(38)
02)
(44)
13.2
23.6
15.9
13.8
6.6
=
Coefficient of variation Field BackgKound samples values Mean Median Mean Median
_
-
.
,.
-
4.0f0.7 (361 1.0f0.2 (361 4.4 f 0.9 (81 3.1 f0.6 (81 12.5 f 3.2 (20) 2.2kO.7 (20) 63,2 (1) 1.010.1 csn
Mean of the ratios of net measurement to background level + SE.
(36f
lOi&.
1.1
71.2rf:Hi.S (32) 49.1 +- 5.0 (15) 11.2f 1.5 (30) 53.6 f 12.4 (41 8.3i 1.5 (281 1.8& 0.5 (281 6.4& 1.3 i (8) 3.0* 1.5 (8) 27.7Jc 4.5 (14) 3.94: 0.7 (14) 10.3* 1.1 (18)
(8)
_
.--,,
25.5* 1.1 17) 9.3%’ 1.9 (15) 5.1 f 1.0 (151 8.0& 1.6 (4) 6.2& 1.8 (4) 33.6 f 10.4 (8) 5.6f 2.6 (8) 3.6+ 0.6 (4) 14.5+ 1.4 (141
133k11.7 (15) 25.9f 5.1 (6) 5.7&- 0.6
Mean seasonal net dry deposition or co~ntration f SE. Fohated Non-foliated neriods Deriods
-__-_^---
pgrn-*h-r SO‘?pgm-ih-t SO:~gm-2h-’ so:pgrn-* h-r soi/lgm-2h-’ SalngmW2h-r SO;Icgm-’ SO:pgmW3 SO,
figm-zh-t XI;pgrn-a h-t SO:~grn-‘h-” SO:-
Reposition and concentration units
Table 3. Statistics describing the dry deposition of sulfate to surrogate surfaces and the ambient concentration of sulfate aerosols and sulfur dioxide. Sample size in parenthesis
8
632
JOHN J. VANDENBERG and KENNETHR. KNOERR
ambient concentration as a function of foliage condition. The coefficient of variation (CV) statistic is calculated as 100 times the standard deviation of sample replicates divided by the mean of the replicates. By relating the magnitude of a sample variance to the sample mean, the CV statistic yields an expression of relative variability that is especial!y useful in comparing the variability of populations with widely differing means (Goldstein, 1967). In nearly every case, the median CV was less than the mean CV, reflecting the effect of an occasional extreme CV value. The median CV provides a more representative statistic for comparison purposes, thus it was employed in the following analysis. The magnitude of the sulfate accumulations on the samplers relative to the initial background or ‘contamination’ level may be expressed as a ratio of net measurement to background level by (I)
This is analagous to the familiar ‘signal to noise’ ratio often used in environmental instrumentation (Fritschen and Gay, 1979). Several conclusions may be drawn about sample replication and the benefits of certain sampling techniques from the median coefficients of variation. For those techniques which had very large median CV values, such as the solid core Teflon downfacing surface, a masking of the true variation in dry deposition rates may be expected. In contrast, for sampling techniques which had a low median CV for exposed samples, such as the filter plate, petri dish, high volume sampler and Huey sulfation plate, a greater level of confidence may be placed in the values obtained due to the high level of replicability. Techniques such as the high-volume, petri dish and bucket inside samplers with relatively high final concentrationsand low initialconcentrations will typically have high ratios from (I), demonstrating less ‘noise’ interference and potentially greater sample precision. Fractional ratios indicate that the magnitude of the measurement after field exposure is similar to the initial background measurement. Interpretation of data from devices with fractional ratios is difficult, especially if the field sample and background measurements are highly variable (as indicated by the coefficients of variation). Thus the ratio of the net accumulation to the background level must be considered in conjunction with the median coefficients of variation for the background and field samples to indicate the degree of uncertainty present in the field data. Data precision
matrix
The coefficients of variation were combined with the ratios from (1) to create the precision matrix shown in Table 4. This matrix enables an assessment of relative precision. with some matrix positions reflecting precise
results in which considerable certainty may be placed, in contrast to other matrix positions which reflect considerable uncertainty. Of greatest imporrattcc to the degree of precision associated with a matrix position are the ratio of net accumulation to background level and the field sample coemcient of variation statistics. For each technique, an assignment to a matrix position was generated by a definition of ‘High‘ and ‘LOW’with respect to the ratio of the net accumulation to background level, the field sample CV, and the background CV (Table 4). From Table 4 it appears that the high-volume and petri dish samplers are in the most desirable matrix positions. The filter plate, Huey sutfation plate and bucket inside samplers are characterized as having fair precision, with considerable uncertainty in the outside deposition buckets and Teflon configurations indicated by their assignment to the least desirable matrix positions. The precision of the filter plate must be considered in light of its correlation with sulfur dioxide concentrations, adequate precision in this case may not indicate adequate sulfate dry deposition accuracy. Deposition velocities Deposition velocities, which represent the surface flux of sulfate normalized by the ambient sulfate concentration, enable a comparison between surfaces and between studies. Mean deposition velocities ( V,) for individual surrogate surfaces exposed within the forest during the foliated season are presented in Table 5. The smooth, upfacing petri dish and Teflon surfaces show consistent deposition velocities of 0.03 cm s- ‘, with the polycarbonate membrane and bucket inside surfaces having a mean V, of 0.10 and 0.11 cm s- I, respectively. The rougher petri dish filter and filter plate surfaces had mean deposition velocities of 0.31 and 0.14cms ‘, respectively. These values demonstrate the apparent effect of texture and geometry on dry deposition velocities, with the rougher petri dish filter receiving a factor of ten higher Vd than the smooth petri dish and Teflon surfaces. Typical dry deposition velocities to various individual surfaces have been reviewed by Garland (1974) and Droppo (1979). The range of values extends from essentially zero to over 1ems-‘, with average deposition velocities around 0.1-0.2 cm s- I. Few studies have been conducted on dry deposition to surfaces exposed in tall forest canopies, or to the forest as a unit. Lindberg and Harriss (1981) reported an average sulfate dry deposition velocity of 0.13 + 0.04cm s- ’ for polycarbonate petri dishes exposed within a deciduous forest. These authors also report that simultaneously exposed petri dishes and oak leaves had a mean sulfate V, of 0.09 and 0.13 cm s- ‘, respectively. Using the same petri dish surfaces, Lindberg and Lovett (1982, pers. comm.) measured an average upper canopy deposition vefocity of O.l6cms- I. All of these values and the values in Table 5 are for individual
Comparison of surrogate surface techniques for estimation of sulfate dry deposition
633
Table 4. Precision matrix for the evaluation of sulfate dry deposition to surrogate surfaces
CV Field Samples Low ( < 10%)
I
High ( 210%)
High Volume
(High Precision)
Filter Plate Huey Plate
Petri Dish Filter
(Medium Precision)
Bucket Outside (Lowest Precision)
The ratio of the net accumulation to background level is defined as “High” if the background measurements comprised no more than 10% of the net deposition, i.e. the ratio was greater than or equal to 10. Similarly, the exposed sample and background level coefficients of variation are defined as ‘High’ for median coefficients of variation greater than or equal to 10%.
Table 5. Mean deposition velocity of sulfate to surrogate surfaces exposed within the forest canopy during foliated periods, f S.E. Surface Filter plate Polycarbonate membrane Petri dish Petri dish filter Bucket inside Bucket outside Steel Teflon upfacing Steel Teflon downfacing Solid Teflon upfacing Solid Teflon downfacing
Mean V, f S.E. (ems-‘) 0.14+0.03 O.lO_+0.03 0.03 + 0.01 0.31 f 0.09 0.11 * 0.03 0.01 * 0.003 0.03 + 0.01 0.01 + 0.003 0.03 f 0.01 0.02 + 0.01
in the forest canopy. With many leaves per unit ground area, these values must be adjusted by the leaf area index to represent the flux to the full forest canopy. Hicks and Wesely (1980), Hicks et al. (1982) and Wesely et al. (1985) used eddy-correlation techniques to measure dry deposition of sulfur to a loblolly pine forest and to the same deciduous forest as used in our study. This technique measures the net effect of the full canopy, not the deposition to individual surfaces. surfaces
Their measurements used half hour averages and ranged from an average sulfur V, of 0.7 cm s-i to the pine forest to negligible deposition to the w~te~ime deciduous forest. A strong pattern of diurnal variation with the forest alternately a sulfur sink and source was observed in these studies. These studies suggest that dry deposition velocities are highly variable, with our study demonstrating that some of the variability is associated with surface texture and geometry. If the deposition velocity to individual surfaces is adjusted by a factor of about eight to estimate the I’, to a full forest canopy with a leaf area index of about five (see next section), then the deposition velocities for every surface type examined in our study will be considerably above the often-used deposition velocity of 0.1 ems-i (Lindberg and Harriss, 1981) and more similar to the higher values reported by Hicks and Wesely (1978, 1980) and Wesely and Hicks (1979). Forest canopy removal
ofpollutants
The geochemical cycle of elements such as sulfur is affected by the rates and mechanisms of dry deposition. Estimates on the quantity of dry deposition to a forest provide an important component of the total cycle, although few studies have directly measured this deposition. Previous studies have found
634
JOHN J. VANDENBERG and KFNNETH R. KNOERK
the majority of the aerosol deposition to be to foliage rather than to the ground surface (Raynor et al., 1974). This deposition to foliage is seen in the decreasing gradient of pollutant concentration from above the forest canopy to the forest floor (Sehmel, 1980). In our Duke Forest study, mean high-volume sulfate concentration gradients normalized to the above-canopy location decreased by 10.2+ 1..5”,, from the abovecanopy position to the forest floor during periods with foliage on the trees. Mean sulfate dry deposition rates averaged from all surfaces decreased by 57.5 + 9.2 o,j from the above-canopy position to the forest floor. Normalized sulfur dioxide concentrations similarly demonstrated a mean decrease of 45.8 + 6.5 ‘II,from the above-canopy sampling level to the forest floor at the same time. These pollutant concentration and deposition rate gradients indicate that the forest is providing a net sink for sulfur pollutants during periods with foliage. Data on the dry deposition rate of sulfate to some ot the surrogate surfaces were used to estimate the potential sink strength of the vegetated canopy. Deposition rates to the petri dish, bucket inside and filter plate surrogate surfaces, which represent the range of surface texture and sample geometry, may provide reasonable bounds for the dry deposition of sulfate to natural surfaces. Summing the deposition to an upfacing surface with the deposition to a downfacing surface (downfacing deposition estimated as 0.31 times upfacing surface deposition based on Teflon data), and multiplying this sum by the mean leaf area index (5.5) yields an estimate of the deposition to the foliage. This deposition estimate, when added to a deposition estimate for a unit ground area. yields the dry sulfate deposition rate to the forest. which is approximately 8.2 times the deposition rate to an individual surface. The estimated dry deposition rates for the foliated 1981 4.0, during were 11.5 and period 21 .Okg SOi- ha- ’ based on the petri dish, bucket inside and filter plate surfaces exposed within the forest, respectively. The much higher value for the filter plate surface may indicate some sulfur dioxide interference. These values compare favorably with the sulfate dry deposition estimate based on polycarbonate petri dishes made by Lindberg et ~11.(1979) of 14.4kg SOi- ha- ’ (foliage of a chestnut oak canopy during 1978) I. Reasons for the difference in petri dish deposition rates between the study by Lindberg ef al. and our study are not known, although the differences may be related to sulfate sources near the Oak Ridge site, different study years, and polystyrene vs polycarbonate construction of the petri dishes. The wide range of surface deposition rates estimated from the variety of deposition surfaces used in this study emphasizes the uncertainty of the surrogate surface measurement techniques as well as the dependency of the dry deposition of sulfate on surface characteristics. In spite of these limitations, surrogate surfaces provide at least an approximate estimate of
sulfate flux rates not currently feasible with natural surfaces. The use of surrogate surfaces can also provide a historical data base of dry deposition for future evaluation. Currently, a critical research need ISstudies emphasizing surface deposition on natural vegetation. Such studies should help to relate the observed deposition on surrogate surfaces in this and other studies to that on natural surfaces. Acknowledgements--.We wish to thank Dr. Steven Lindberg, Dr. Daniel Richter, Dr. William Schlesinger and the manuscript reviewers for helpful comments and suggestions. Dr. Jack Durham, Dr. Lester Spiller and Dr. Joseph Sickles facilitated project support through equipment use and throuah EPA Grant No. R-806393 and RTI Purchase Orders No. 21407 and No. 26684
REFERENCES
Attiwill P. M. (1966)The chemical composition of rainwater in relation to cycling of nutrients in a mature eucalyptus forest. Plant Soil 24, 390-406.
Axelrod H. D., Teck R. J. and Lodge J. P., Jr. (1971) Further study on prefilter interference for sulfur dioxide measurements. J. Air Polka. Control Ass. 21, 218. Davidson C. 1. (1977) Deposition of trace-metal-containing aerosols on smooth, flat surfaces and wild oat grass. Ph.D. dissertation. California Institute of Technology, Los Angeles, CA. Droppo J. G. (1974) Dry deposition processes on vegetation canopies. In Atmosphere-St&ace Exchange of Particulate and Gaseous Pollutants (edited by Engelmann R. J. and Sehmel G. A.), pp. 104-l 11. ERDA Conf.- 740921. Droppo J. G. (1979) Experimental techniques for dry deProc. Symp. on Potential position measurements. Environmental and Health Efects of Atmospheric Sulfur Deposition. Gatlinburg, TN, 14-18 October 1979.
Eisenbud M. and Harlev J. H. (1955) Radioactive fallout in the United States. Science, Wash. lil, 677680. Everett R. G., Hicks B. B., Berg W. W. and Winchester J. W. (1979) An analysis of particulate sulfur and lead gradient data collected at Argonne National Laboratory. Atmospheric Environment 13, 1361-1368.
Forrest J. and Newman L. (1973) Ambient air monitoring for sulfur compounds. J. Air Polka. Control Ass. 23, 761. Fritschen L. J. and Gay L. W. (1979) Environmental Instrumentation. Springer. New York. Garland J. A. (1974)Dry deposition of SO, and other gases. In Atmosphere&$aceE&hange of Particulate and Gaseous PoWants (edited bv Eneelmann R. J. and Sehmel G. A.),
pp. 2122227. ERDA Co;f.-740921. Goldstein A. (1967) Biostatistics: An Introductory Course. Macmillan, New York. Heesen T. C.. Young D. R. and McDermott-Erlich D. (1979) Evaluation of a technique for measuring dry aerial deposition rates of DDT and PCB residues. Atmospheric Environment 13, 1677-1680.
Hicks 8. B. and Wesely M. L. (1978) An examination of some micrometeorological methods for measuring dry deposition. US. EPA Report EPA-6C0/7-78-116. Hicks B. B. and Wesely M. L. (1980) Turbulent transfer processes to a surface and interaction with vegetation. In Atmospheric Sulfur Deposition (edited by Shriner D. S., Richmond C. R. and Lindberg S. E.), pp. 199207. Ann Arbor Press, Ann Arbor, MI Hicks B. B., We&y M. L. and Durham J. L. (1980) Critique of methods to measure dry deposition: Workshop summary. U.S. Environmental Sciences Research Laboratory, Research Triangle Park, NC.
Comparison of surrogate surface techniques for estimation of sulfate dry deposition Hicks B. B., Wesely M. L., Durham 1. L. and Brown M. A. (1982) Some direct measurements of atmospheric sulfur fluxes over a pine plantation. Atmospheric Environment 16, 2899-2903. Hicks B. B. (1983) Dry deposition processes. The acidic deposition phenomenon and its effects, A-7. EPA-600/883-016A (Draft). Hosker R. P., Jr. and Lindberg S. E. (1982) Review: atmospheric deposition and plant assimilation of gases and particles. hospheric E&ronment 16, 88%910: Lindbera S. E.. Harriss R. C.. Turner R. R.. Shriner D. S. and Huff b. D. (1979) Mechanisms and rates of atmospheric deposition of selected trace elements and sulfate to a deciduous forest watershed. Oak Ridge National Laboratory Report ORNL/TM-6674. Lindberg S. E. and Harriss R. C. (1981) The role of atmospheric deposition in an eastern U.S. deciduous forest. Wat. Air Soil Pollut. 16, 13-31. Little P. (1977) Dewsition of 2.75.5.0 and 8.5 urn Darticles to plant and s&l s&faces. Enuir. Pollut. 12, 243-jO5. McCall J. G. and Bush D. S. (1978) Precioitation and throughfall chemistry in the Sah F&cisco’Bay area. J. Enoir. Qual. 7, 352-357.
Munn R. E. and Bolin B. (1971) Review: global air pollutionmeteorological aspects. Atmospheric Environment 5, 363-402.
Nihlgard B. (1970) Precipitation, its chemical composition
635
and effect on soil water in a beech and spruce. forest in south Sweden. Oikos 21, 208-217. NOAA (1981, 1982) National Oceanic and Atmospheric Administration. Environmental Data and Information Service, National Climatic Center, Asheville, NC. Local Climatological Data, Monthly Summary for RaleighDurham Airport, NC. Raynor G. S., Hayes J. V. and Ogden E. C. (1974) Particulate dispersion into and within a forest. Boundary-Layer Met. 7, 429-456.
Sandberg J. S., Levaggi D. A., DeMandel R. E. and Siu W. (1976)Sulfate and nitrate oarticulates as related to SO, and NOI ‘gases and emissions. J. Air Polk. Control As;. 26, 559-564.
Schlesinger W. and Reiners W. (1974) Deposition of water and cations on artificial foliar collectors in fir-krummhoiz of New England Mountains. Ecology 55,378-386. Sehmel G. A. (1980) Particle and gas dry deposition: a review. Atmospheric Environment 14,983-1011. Wesely M. L. and Hicks B. B. (1979) Dry deposition and emission of small particles at the surface of the earth. hoc. Fourth
Symp. on Turbulence,
Dijiiion
and Air Quality.
Reno, NV, 15-18 January. Am. Met. Sot., Boston, MA, pp. 510-513. Wesely M. L., Cook D. R. and Hart R. L. (1985)Fluxes of gases and particles above a deciduous forest in wintertime. Boundary-Layer Met. (in press).
in Gnat
Vol. 19, No. 4, pp. 627435,
@X4-5981/85
1985 0
Britain.
$3.00 + 0.00
1985 Pergamon
Press Ltd.
COMPARISON OF SURROGATE SURFACE TECHNIQUES FOR ESTIMATION OF SULFATE DRY DEPOSITION* JOHNJ.VANDENBERG~~~
KENNETH
R.KNOERR
School of Forestry and Environmental Studies, Duke University, Durham, NC 27706, U.S.A. (First received 14 October 1983 and
infinalform
23 July 1984)
Abstract-The dry deposition rates of sulfate particles to artificial surfaces within and above a mature hardwood forest were measured over an annual range of synoptic weather conditions. Artificial, or ‘surrogate’, surfaces representing both rough and smooth textural types included deposition buckets, petri dishes, filter paper, Teflon configurations and polycarbonate membranes. Ambient concentrations of sulfate and sulfur dioxide were also monitored. The artificial surfaces were evaluated on the basis of the magnitude of the sulfate dry deposition rates and measurement precision. Correlations between techniques and the magnitude of the deposition velocities identified technique similarities. Ambient concentrations of the sulfur oxides and the deposition rates were not well correlated. For diverse reasons, many of the techniques were found to have limited reliability. The petri dish, bucket inside and filter plate surfaces were found to represent the most precise devices for the estimation of dry deposition to smooth, complex and rough artificial surfaces, respectively. Seasonal averages for samplers exposed at all heights were 11.2, 27.7 and 71.2 pg SO:- mm2 h- ‘, yielding mean deposition velocities to surfaces exposed within the forest canopy of 0.03,O.11 and 0.14cm s- ’ and an annual estimate of the potential dry deposition to a foliated hardwood forest of 4.0, 11.5 and 21.0 kgSO:- ha-’ for the petri dish, bucket inside and filter plate surfaces, respectively. The indirect ratio between deposition rates and velocities results from varying concentrations of ambient sulfate between sampling periods. The accuracy of the filter plate data is suspect due to a significant correlation with sulfur dioxide concentrations. Sulfur concentration and deposition rate gradients indicate the forest is providing a net sink for sulfur pollutants during periods with foliage. The wide range of dry deposition rates estimated from the variety of deposition surfaces emphasizes the uncertainty of the artificial surface measurement techniques. In spite of these limitations, surrogate surfaces provide an estimate of sulfate flux rates not currently obtainable from natural surfaces. Key
word
index: Dry deposition, sulfate, air pollution, forest.
restricted use due to stringent site requirements, expense and sampling problems (Garland, 1974; Droppo, 1979). Dry deposition has also been estimated on the basis
INTRODUCTION Vegetation pollutants deposition
may provide an important sink for air through the absorption of gases and the of substances in rainfall and dryfall. When
of ‘surrogate’ collecting surfaces. Surrogate collectors are potentially useful in that they provide a common surface available for application in a variety of environments which avoid the problems of uptake or leaching from plant parts. Surrogate surfaces which have been used in dry deposition studies include sampling devices such as open buckets, petri dishes, Teflon, coated and uncoated glass, filter paper, plastic nets and artificial foliage (Hicks et al., 1980; Eisenbud and Harley, 1955; Nihlgard, 1970; Heesen et al., 1979; Schlesinger and Reiners, 1974). For each of these surrogates, the processes acting to deposit material may be affected by the particle attraction and capture characteristics of its surface and by the local turbulence induced by its size and Shape (Munn and Bolin, 1971). Differences in size and shape, and therefore in the rate of dry deposition, among various surrogate surfaces and natural surfaces have severely limited the extrapolation of data from one surface type to another (Hosker and Lindberg, 1982; Droppo, 1974). While previous work has shown that dry deposition to both surrogate and natural surfaces is directly related to
attempts have been made to estimate dry deposition via leaf washing techniques, they have proven to be of limited value for pollutants such as sulfate and nitrate. These compounds are plant nutrients, which can move across the cuticle of plant leaf tissues. In these estimates there is considerable uncertainty about what portion is dry deposition and what portion has been derived from an internal plant pool (Attiwill, 1966; McCall and Bush, 1978; Lindberg et al., 1979). As an alternative, some field measurements have used meteorological methods to estimate the mass transfer of pollutants to plant canopies. Of these approaches, the gradient and eddy-correlation techniques show promise in estimating total mass flux from the atmosphere to a forest canopy (Everett et al., 1979; Hicks et
al.,
1982). However,
these techniques
have
*This study was a cooperative effort of the Duke University School of Forestry and Environmental Studies, the Aerosol Research Branch of the U.S. Environmental Protection Agency, and the Research Triangle Institute. 627
628
JOHN J. VANDENBERG and KENNETH R. KN~ERK
wind velocity under wind tunnel conditions (Little, 1977) little information is available from the more complex conditions in field experiments. The present study evaluates the dry deposition ot sulfate to a variety of surrogate surfaces, and provides a basis for comparison of these surfaces. The surrogate sampling surfaces were deptoyed within and above a mature deciduous forest to evaluate dry deposition at different canopy levets. Sulfate dry deposition velocities to the surrogate surfaces,and net canopy removal of particulate sulfate were calculated. Samples were collected periodically from January 1981 to April 1982, to evaluate the effects of seasonal changes in vegetation and weather conditions. METHODS
The research site was located in the Blackwood Division of the Duke Forest, situated in the gently rolling central Piedmont of North Carolina, about 16 km west of Durham, The surrogate sampling devices were depioyed on a 40-m meteorologicaf tower that extends through and above a 25- to 28-m mixed deciduous forest. The dominant tree species include white oak (Quercus &a), hickory (Caryu spp.) and tulip poplar (Liriodendron tutiperi$em) in the overstory and dogwood (Cornusjforida) in the understory. Sample collection and analysis
Replicatepairs of surrogate surfaceswere deployed at each of the four sampling levels within and above the forest canopy. The sampling levels were at heights of 1, 12, 25 and 36m above the forest floor, corresponding with the forest floor region, the region between overstory and understory canopies, the area of overstory canopy closure, and above the forest foliage, respectively. Surrogate surfaces representing both rough and smooth textural types included 28.6sm diameter ~lyethylene deposition buckets, 9cm diameter polystyrene petri dishes with and without Whatman 41 cellulose filters taped inside, 9-cm wide by 27-cm long Teflon sheets in both solid bar form and as Teflon sheets affixed to a stainless steel core, 4.7-cm diameter Nuclepore No. 111105 polycarbonate membranes held in circular filter holders, and a sheet of Pallflex E70207SW cellulose-glass filter paper held within a stainless steel frame to expose a 13.2 x 182cm rectangular portion of filter paper. During surface sampling periods simultaneous measurement of the ambient concentrations of sulfate and sulfur dioxide were monitored at the top and bottom of the tower with U.S. EPA high-volume samplers and Huey sulfation plates, respectively. For periods when on-site, highvolume samples were not available, ambient sulfate concentrations were measured by the Research Triangle Institute (RTI), Research Triangle Park, N.C., some 22 km away. Comparison of simultaneous high-volume measurements made at the Duke Forest and RTI sites demonstrated a strong correlation (r* = 0.93) between the ambient sulfate concentrations at these locations. Prior to deployment on the tower, the bucket and Teflon surfaces were thoroughly washed with deionized water and dried with ethanol. The other surfaces and filters were used directly from the manufacturer, with any frame or material in contact with the collection surfaces cleaned with deionized water and ethanol. During the preparation and extraction of the sampies, all equipment was handled using polyethylene
glovesand cleaned thoroughly to avoid contamination. At the end of each exposure period, the sampiers wereremoved from the tower and returned in a clean carrier box to a field laboratory for extraction. Surface samples were extracted
using known volumes ol’ eluent (0.003 M HCC,. 0.0024 M CO:- 1, and transported in clean polypropylene bottles to the laboratories for analysis. Samples collected during this project were analyzed for sulfate (SO: ) concentrations by the EPA and RTI laboratories using standard ion chromatography techniques. Analysis of system accuracy, based on US. primary standards, indicated an average accuracy for the RTI laboratory of & 2 “, and an average precision of f 3 9, over a wide range of concentrations. The EPA laboratory was not required to process blind primary standards, although a test of system accuracy at the end of the experimental period indicated an accuracy of rf. 15Yo. Statistical analysis for each sampling device mcluded a calculation of univariate statistics on a seasonal basis, with deposition velocities in units of ems-’ calculated for each exposure period by dividing the deposition rate (pgcm ’ s ‘) by the ambient sulfate concentration bgm-“). A correlation coefficient matrix was developed which related each sampling device to every other one. The rate of sulfate deposition to some of the surrogate surfaces was used to estimate pollutant removal by the forest canopy through a caiculation of the total flux rate to a typical multilayered canopy. The total flux rate is equal to the summation of the deposition on upward and downward facing surfaces (taking the leaf area index into account) plus the ground flux, with each component expressed per unit ground area. This analysis assumes that the flux rates to the smooth and rough surrogate surfaces encompass the range of flux rates expected for a leaf surface. Summing upward and downward surfaces within the canopy attempts to simulate the actual deposition on leaves which experience impaction of particles on all surfaces. RESULTS AND DISCUSSION
Initial experiments indicated that for some of the sampling surfaces a dry deposition period of at least two days was necessary to distinguish an a~umu~ation of sulfate above background levels. Thus the sample periods were kept as long as feasible, averaging 86 h (range 24- 143; N = 13). Twenty-nine attempts were made to collect dry deposition. Of these, thirteen were successfully completed without a precipitation event. However, during five of the thirteen periods the local climatological record indicated the potential for nocturnal dew formation (r.h. 2 9Sj10) (NOAA, 1981, 1982). Comparison of the deposition rates during periods with and without potential dew formation did not indicate substantial profile differences. Thus, while dew formation may have enhanced the deposition rates during some periods through aerosol nucleation and coalescence and Stefan flow, the effect was believed to be relatively minor (Hicks, 1983). Two periods with very slight rainfalls of 1.3 and 0.2 mm (6 0.05 in and 4 0.01 in, respectively) were also analyzed to provide examples of sulfate deposition with minor precipitation events. Both of these minor rainfall periods displayed deposition rates at least an order of magnitude greater than typical dry deposition rates, with the smallest rainfall event having the highest flux rate. These results show that even very small amounts of precipitation can contaminate dry deposition sampies. Periods with rainfail events were therefore excluded from further anaiysis.
Solid
- 0.02
0.50
0X2*
0.13
0.33
0.81*
0.73**
0.24
-0.06 -0.27
0.42*
0.06 -0.14
0.82**
0.65*
0.57
0.01 0.34
0.32 0.52
0.15
0.25 0.41
0.43
-0.62 0.37
- 0.47 -0.21
downfacing
Teflon
- 0.23 -0.20
Bucket inside
0.48
0.28
0.10 0.02
0.14 0.52
-0.15 0.31
Solid Teflon upfacing
0.69**
0.53** 0.55
0.36* 0.34
- 0.26 0.33*
Steel Teflon downfacing
.. -
_.
.,.
-. .
.“,
-
-I
,.
-
--
-_
0.65** 0.77**
0.29 0.72**
0.06 0.09
steel Teflon upfacing
*One asterisk indicates significant coefficients at the P G 0.05 level, two asterisks at the P < 0.01 level.
High volume Huey sulfation plate Filter plate Polycarbonate membrane Petri dish Petri dish filter Steel Teflon upfacing Steel Teflon downfacing Solid Teflon upfacing Solid Teflon downfacing Bucket inside
Bucket outside
_-
-,.
0.97**
0.68* 0.81*
0.31 -0.34
Petri dish filter
-..
-0.21 0.58**
0.15 0.00
Petri dish
Table I. Correlation coefficient matrix for sulfate dry deposition to surrogate surfaces
-
,” ._
0.22
0.52 0.18
Polycarbonate membrane
. .._..
0.34 0.65**
Filter piate
_.
._.
0.13
Huey sulfation plate
630 Correlation
JOHN J. VANDENBERG and KENNETH K. KNOERR
coeficients
Correlation coefficients calculated for the dry deposition rate of sulfate to the various surrogate surfaces were generally positive and often significant (Table 1). In general, the significant correlations were found between surfaces with a similar texture or geometry, with the highest correlation coefficients for any device being with that device used in another way. Thus, the smooth, low profile Teflon, petri dish and polycarbonate membrane surfaces were highly correlated with each other. The smooth bucket inside and outside surfaces with their greater profile in each dimension had highest correlations with each other and with the smooth Teflon surfaces. The relatively rough texture and low profile of the filter plate surface showed highest correlation with the similarly textured petri dish filter surface. From this pattern of correlations it may be concluded that the primary factor controlling the dry deposition rate of sulfate to surrogate surfaces is the texture and geometry of the sampling device. There was some redundancy in Teflon deposition surfaces. The use of different construction materials was intended to determine if the dry deposition rate of sulfate to Teflon was significantly affected by electrostatic effects. Mean deposition rates to the solid core and steel core Teflon surfaces were very similar in magnitude, with a t-test of similarly-oriented faces showing no significant differences between the means. Thus, any electrostatic effects related to the construction of the Teflon surfaces did not significantly affect the dry deposition rate of sulfate to Teflon, similar to conclusions of Davidson (1977) and Droppo (1974). One deposition surface, the filter plate, had a highly significant correlation with the ambient concentration of sulfur dioxide. This may reflect the effect of SO2 absorption on the formation of extrinsic sulfate on the cellulose-glass filter paper surface. Axelrod et al. (1971) have reported sulfate artifact formation on alkaline glass fiber reaction sites, with a corrective pretreatment procedure suggested by Forrest and Newman (1973). The filter paper used in the present project was not treated prior to tower deployment, thus the flux rates reported for this surface must be considered suspect and likely indicating the deposition of particulate sulfate with some sulfur dioxide interference. A comparison between the techniques for measuring ambient concentrations of sulfate and sulfur dioxide, i.e. the high-volume sampler and Huey sulfation plate, revealed that the ambient concentrations of sulfate and sulfur dioxide were poorly correlated (r = 0.13). This contrasts with Sandberg et al., (1976) who found a correlation coefficient of 0.70 between the sulfur species. However, Sandberg’s correlation was determined on a mean annual basis, which effectively damped out any direct, day to day variations that were associated with our study. While we expected a correlation between dry deposition and ambient concentration of sulfates, such a
correlation was not found in our experimental data. We feel that this lack of correlation may have at least two causes. The first is that the ambient \ulfate concentrations had only a limited range of values ov’er the series of sampling periods. The second is that we had to expose our sampling devices for a several days period (usually 2~4 days) to obtain measurable quantities of deposited material. During each ot‘ these sampling periods there may have been variation in the ambient concentration of sulfate as well as diurnal variation in atmospheric stability and wind speed which affected the deposition process. When there is variation in both concentration and turbulence processes affecting deposition during a sampling period, the average deposition may be poorly correlated with the average ambient concentration. While not reported we also tested the correlation between deposition and average wind velocity during the sampling periods. This correlation was also insignificant, we believe, for the same reasons that the was with ambient concentration correlation insignificant. Sample variability
Multivariate analysis of variance was used to assess the major sources of data variability. The two scales of spatial variability (i.e. the variability between simultaneously exposed replicate samples and the variability associated with vertical distance from the forest floor) were compared to each other and to the temporal variability. The variability in the deposition rate associated with the vertical position and sampling date factors was usually found to be highly significant and similar in magnitude as demonstrated by the petri dish data in Table 2. The variability associated with these factors was also much larger than the variability associated with the two replicate samples at each level. These results suggest that the analytical and sampling variability provide relatively small contributions to the total observed variability. In addition, with the vertical and temporal variability components generally of the same magnitude, the data set generated in this project may be represented by statistics averaged across space and time. For each sampling technique, results are presented in Table 3 on the mean and median coefficient of variation (CV), sample size, ratio of net measurement to background level and mean dry deposition rate or Table 2. Three way analysis ofvarrance of the petri dish data Contribution to total variation Source of variation
( “,,I
df’
I
Replicate Date Position Date *position
0.2 37.2 1x.9 43.6
1
0.51
9 3 27
5.42* x.22* 7.1 If ___
*Asterisks indicate significant sources of variation at the P < 0.05 level; d.f; degrees of freedom: F, F-value.
-..,-
,,
-
Filter giate Polycarbonate membrane Petri dish Petri dish filter Steel Teflon upfacing Steel Teflon do~nf~ing Solid Teflon upfacing Solid Teflon downfacing Bucket inside Bucket outside High volume sampler Huey sulfation piate
Surface or T~hniqu#
_
_
-
_
.,.
_
,_
_
-
.,,
7.3
-
10.8
f5) (471
12.1
_-
-
f121
(2) 9.0
(8’ 33.3 (12) 23.2 18.0 (12) 4.4 4.4
34.4
35.9 “I) 21.6 (18) 29.0 19.1 S8) 3.0 2.4
42.4
(8)
41.6
41.7
41.6
(11) *
7.0
17.6
6.9
9.0
t2) 2Q.6 s2t 31.5 24.0 (121 31.1 27.7
(10)
(20)
(12)
36.7
48.5
7.0
16.6
22.5 (I’) 15.9 (40) 32.1 23.2 (44) 33.9 28.7
9.5
13.2
3.6
7.0
(38)
02)
(44)
13.2
23.6
15.9
13.8
6.6
=
Coefficient of variation Field BackgKound samples values Mean Median Mean Median
_
-
.
,.
-
4.0f0.7 (361 1.0f0.2 (361 4.4 f 0.9 (81 3.1 f0.6 (81 12.5 f 3.2 (20) 2.2kO.7 (20) 63,2 (1) 1.010.1 csn
Mean of the ratios of net measurement to background level + SE.
(36f
lOi&.
1.1
71.2rf:Hi.S (32) 49.1 +- 5.0 (15) 11.2f 1.5 (30) 53.6 f 12.4 (41 8.3i 1.5 (281 1.8& 0.5 (281 6.4& 1.3 i (8) 3.0* 1.5 (8) 27.7Jc 4.5 (14) 3.94: 0.7 (14) 10.3* 1.1 (18)
(8)
_
.--,,
25.5* 1.1 17) 9.3%’ 1.9 (15) 5.1 f 1.0 (151 8.0& 1.6 (4) 6.2& 1.8 (4) 33.6 f 10.4 (8) 5.6f 2.6 (8) 3.6+ 0.6 (4) 14.5+ 1.4 (141
133k11.7 (15) 25.9f 5.1 (6) 5.7&- 0.6
Mean seasonal net dry deposition or co~ntration f SE. Fohated Non-foliated neriods Deriods
-__-_^---
pgrn-*h-r SO‘?pgm-ih-t SO:~gm-2h-’ so:pgrn-* h-r soi/lgm-2h-’ SalngmW2h-r SO;Icgm-’ SO:pgmW3 SO,
figm-zh-t XI;pgrn-a h-t SO:~grn-‘h-” SO:-
Reposition and concentration units
Table 3. Statistics describing the dry deposition of sulfate to surrogate surfaces and the ambient concentration of sulfate aerosols and sulfur dioxide. Sample size in parenthesis
8
632
JOHN J. VANDENBERG and KENNETHR. KNOERR
ambient concentration as a function of foliage condition. The coefficient of variation (CV) statistic is calculated as 100 times the standard deviation of sample replicates divided by the mean of the replicates. By relating the magnitude of a sample variance to the sample mean, the CV statistic yields an expression of relative variability that is especial!y useful in comparing the variability of populations with widely differing means (Goldstein, 1967). In nearly every case, the median CV was less than the mean CV, reflecting the effect of an occasional extreme CV value. The median CV provides a more representative statistic for comparison purposes, thus it was employed in the following analysis. The magnitude of the sulfate accumulations on the samplers relative to the initial background or ‘contamination’ level may be expressed as a ratio of net measurement to background level by (I)
This is analagous to the familiar ‘signal to noise’ ratio often used in environmental instrumentation (Fritschen and Gay, 1979). Several conclusions may be drawn about sample replication and the benefits of certain sampling techniques from the median coefficients of variation. For those techniques which had very large median CV values, such as the solid core Teflon downfacing surface, a masking of the true variation in dry deposition rates may be expected. In contrast, for sampling techniques which had a low median CV for exposed samples, such as the filter plate, petri dish, high volume sampler and Huey sulfation plate, a greater level of confidence may be placed in the values obtained due to the high level of replicability. Techniques such as the high-volume, petri dish and bucket inside samplers with relatively high final concentrationsand low initialconcentrations will typically have high ratios from (I), demonstrating less ‘noise’ interference and potentially greater sample precision. Fractional ratios indicate that the magnitude of the measurement after field exposure is similar to the initial background measurement. Interpretation of data from devices with fractional ratios is difficult, especially if the field sample and background measurements are highly variable (as indicated by the coefficients of variation). Thus the ratio of the net accumulation to the background level must be considered in conjunction with the median coefficients of variation for the background and field samples to indicate the degree of uncertainty present in the field data. Data precision
matrix
The coefficients of variation were combined with the ratios from (1) to create the precision matrix shown in Table 4. This matrix enables an assessment of relative precision. with some matrix positions reflecting precise
results in which considerable certainty may be placed, in contrast to other matrix positions which reflect considerable uncertainty. Of greatest imporrattcc to the degree of precision associated with a matrix position are the ratio of net accumulation to background level and the field sample coemcient of variation statistics. For each technique, an assignment to a matrix position was generated by a definition of ‘High‘ and ‘LOW’with respect to the ratio of the net accumulation to background level, the field sample CV, and the background CV (Table 4). From Table 4 it appears that the high-volume and petri dish samplers are in the most desirable matrix positions. The filter plate, Huey sutfation plate and bucket inside samplers are characterized as having fair precision, with considerable uncertainty in the outside deposition buckets and Teflon configurations indicated by their assignment to the least desirable matrix positions. The precision of the filter plate must be considered in light of its correlation with sulfur dioxide concentrations, adequate precision in this case may not indicate adequate sulfate dry deposition accuracy. Deposition velocities Deposition velocities, which represent the surface flux of sulfate normalized by the ambient sulfate concentration, enable a comparison between surfaces and between studies. Mean deposition velocities ( V,) for individual surrogate surfaces exposed within the forest during the foliated season are presented in Table 5. The smooth, upfacing petri dish and Teflon surfaces show consistent deposition velocities of 0.03 cm s- ‘, with the polycarbonate membrane and bucket inside surfaces having a mean V, of 0.10 and 0.11 cm s- I, respectively. The rougher petri dish filter and filter plate surfaces had mean deposition velocities of 0.31 and 0.14cms ‘, respectively. These values demonstrate the apparent effect of texture and geometry on dry deposition velocities, with the rougher petri dish filter receiving a factor of ten higher Vd than the smooth petri dish and Teflon surfaces. Typical dry deposition velocities to various individual surfaces have been reviewed by Garland (1974) and Droppo (1979). The range of values extends from essentially zero to over 1ems-‘, with average deposition velocities around 0.1-0.2 cm s- I. Few studies have been conducted on dry deposition to surfaces exposed in tall forest canopies, or to the forest as a unit. Lindberg and Harriss (1981) reported an average sulfate dry deposition velocity of 0.13 + 0.04cm s- ’ for polycarbonate petri dishes exposed within a deciduous forest. These authors also report that simultaneously exposed petri dishes and oak leaves had a mean sulfate V, of 0.09 and 0.13 cm s- ‘, respectively. Using the same petri dish surfaces, Lindberg and Lovett (1982, pers. comm.) measured an average upper canopy deposition vefocity of O.l6cms- I. All of these values and the values in Table 5 are for individual
Comparison of surrogate surface techniques for estimation of sulfate dry deposition
633
Table 4. Precision matrix for the evaluation of sulfate dry deposition to surrogate surfaces
CV Field Samples Low ( < 10%)
I
High ( 210%)
High Volume
(High Precision)
Filter Plate Huey Plate
Petri Dish Filter
(Medium Precision)
Bucket Outside (Lowest Precision)
The ratio of the net accumulation to background level is defined as “High” if the background measurements comprised no more than 10% of the net deposition, i.e. the ratio was greater than or equal to 10. Similarly, the exposed sample and background level coefficients of variation are defined as ‘High’ for median coefficients of variation greater than or equal to 10%.
Table 5. Mean deposition velocity of sulfate to surrogate surfaces exposed within the forest canopy during foliated periods, f S.E. Surface Filter plate Polycarbonate membrane Petri dish Petri dish filter Bucket inside Bucket outside Steel Teflon upfacing Steel Teflon downfacing Solid Teflon upfacing Solid Teflon downfacing
Mean V, f S.E. (ems-‘) 0.14+0.03 O.lO_+0.03 0.03 + 0.01 0.31 f 0.09 0.11 * 0.03 0.01 * 0.003 0.03 + 0.01 0.01 + 0.003 0.03 f 0.01 0.02 + 0.01
in the forest canopy. With many leaves per unit ground area, these values must be adjusted by the leaf area index to represent the flux to the full forest canopy. Hicks and Wesely (1980), Hicks et al. (1982) and Wesely et al. (1985) used eddy-correlation techniques to measure dry deposition of sulfur to a loblolly pine forest and to the same deciduous forest as used in our study. This technique measures the net effect of the full canopy, not the deposition to individual surfaces. surfaces
Their measurements used half hour averages and ranged from an average sulfur V, of 0.7 cm s-i to the pine forest to negligible deposition to the w~te~ime deciduous forest. A strong pattern of diurnal variation with the forest alternately a sulfur sink and source was observed in these studies. These studies suggest that dry deposition velocities are highly variable, with our study demonstrating that some of the variability is associated with surface texture and geometry. If the deposition velocity to individual surfaces is adjusted by a factor of about eight to estimate the I’, to a full forest canopy with a leaf area index of about five (see next section), then the deposition velocities for every surface type examined in our study will be considerably above the often-used deposition velocity of 0.1 ems-i (Lindberg and Harriss, 1981) and more similar to the higher values reported by Hicks and Wesely (1978, 1980) and Wesely and Hicks (1979). Forest canopy removal
ofpollutants
The geochemical cycle of elements such as sulfur is affected by the rates and mechanisms of dry deposition. Estimates on the quantity of dry deposition to a forest provide an important component of the total cycle, although few studies have directly measured this deposition. Previous studies have found
634
JOHN J. VANDENBERG and KFNNETH R. KNOERK
the majority of the aerosol deposition to be to foliage rather than to the ground surface (Raynor et al., 1974). This deposition to foliage is seen in the decreasing gradient of pollutant concentration from above the forest canopy to the forest floor (Sehmel, 1980). In our Duke Forest study, mean high-volume sulfate concentration gradients normalized to the above-canopy location decreased by 10.2+ 1..5”,, from the abovecanopy position to the forest floor during periods with foliage on the trees. Mean sulfate dry deposition rates averaged from all surfaces decreased by 57.5 + 9.2 o,j from the above-canopy position to the forest floor. Normalized sulfur dioxide concentrations similarly demonstrated a mean decrease of 45.8 + 6.5 ‘II,from the above-canopy sampling level to the forest floor at the same time. These pollutant concentration and deposition rate gradients indicate that the forest is providing a net sink for sulfur pollutants during periods with foliage. Data on the dry deposition rate of sulfate to some ot the surrogate surfaces were used to estimate the potential sink strength of the vegetated canopy. Deposition rates to the petri dish, bucket inside and filter plate surrogate surfaces, which represent the range of surface texture and sample geometry, may provide reasonable bounds for the dry deposition of sulfate to natural surfaces. Summing the deposition to an upfacing surface with the deposition to a downfacing surface (downfacing deposition estimated as 0.31 times upfacing surface deposition based on Teflon data), and multiplying this sum by the mean leaf area index (5.5) yields an estimate of the deposition to the foliage. This deposition estimate, when added to a deposition estimate for a unit ground area. yields the dry sulfate deposition rate to the forest. which is approximately 8.2 times the deposition rate to an individual surface. The estimated dry deposition rates for the foliated 1981 4.0, during were 11.5 and period 21 .Okg SOi- ha- ’ based on the petri dish, bucket inside and filter plate surfaces exposed within the forest, respectively. The much higher value for the filter plate surface may indicate some sulfur dioxide interference. These values compare favorably with the sulfate dry deposition estimate based on polycarbonate petri dishes made by Lindberg et ~11.(1979) of 14.4kg SOi- ha- ’ (foliage of a chestnut oak canopy during 1978) I. Reasons for the difference in petri dish deposition rates between the study by Lindberg ef al. and our study are not known, although the differences may be related to sulfate sources near the Oak Ridge site, different study years, and polystyrene vs polycarbonate construction of the petri dishes. The wide range of surface deposition rates estimated from the variety of deposition surfaces used in this study emphasizes the uncertainty of the surrogate surface measurement techniques as well as the dependency of the dry deposition of sulfate on surface characteristics. In spite of these limitations, surrogate surfaces provide at least an approximate estimate of
sulfate flux rates not currently feasible with natural surfaces. The use of surrogate surfaces can also provide a historical data base of dry deposition for future evaluation. Currently, a critical research need ISstudies emphasizing surface deposition on natural vegetation. Such studies should help to relate the observed deposition on surrogate surfaces in this and other studies to that on natural surfaces. Acknowledgements--.We wish to thank Dr. Steven Lindberg, Dr. Daniel Richter, Dr. William Schlesinger and the manuscript reviewers for helpful comments and suggestions. Dr. Jack Durham, Dr. Lester Spiller and Dr. Joseph Sickles facilitated project support through equipment use and throuah EPA Grant No. R-806393 and RTI Purchase Orders No. 21407 and No. 26684
REFERENCES
Attiwill P. M. (1966)The chemical composition of rainwater in relation to cycling of nutrients in a mature eucalyptus forest. Plant Soil 24, 390-406.
Axelrod H. D., Teck R. J. and Lodge J. P., Jr. (1971) Further study on prefilter interference for sulfur dioxide measurements. J. Air Polka. Control Ass. 21, 218. Davidson C. 1. (1977) Deposition of trace-metal-containing aerosols on smooth, flat surfaces and wild oat grass. Ph.D. dissertation. California Institute of Technology, Los Angeles, CA. Droppo J. G. (1974) Dry deposition processes on vegetation canopies. In Atmosphere-St&ace Exchange of Particulate and Gaseous Pollutants (edited by Engelmann R. J. and Sehmel G. A.), pp. 104-l 11. ERDA Conf.- 740921. Droppo J. G. (1979) Experimental techniques for dry deProc. Symp. on Potential position measurements. Environmental and Health Efects of Atmospheric Sulfur Deposition. Gatlinburg, TN, 14-18 October 1979.
Eisenbud M. and Harlev J. H. (1955) Radioactive fallout in the United States. Science, Wash. lil, 677680. Everett R. G., Hicks B. B., Berg W. W. and Winchester J. W. (1979) An analysis of particulate sulfur and lead gradient data collected at Argonne National Laboratory. Atmospheric Environment 13, 1361-1368.
Forrest J. and Newman L. (1973) Ambient air monitoring for sulfur compounds. J. Air Polka. Control Ass. 23, 761. Fritschen L. J. and Gay L. W. (1979) Environmental Instrumentation. Springer. New York. Garland J. A. (1974)Dry deposition of SO, and other gases. In Atmosphere&$aceE&hange of Particulate and Gaseous PoWants (edited bv Eneelmann R. J. and Sehmel G. A.),
pp. 2122227. ERDA Co;f.-740921. Goldstein A. (1967) Biostatistics: An Introductory Course. Macmillan, New York. Heesen T. C.. Young D. R. and McDermott-Erlich D. (1979) Evaluation of a technique for measuring dry aerial deposition rates of DDT and PCB residues. Atmospheric Environment 13, 1677-1680.
Hicks 8. B. and Wesely M. L. (1978) An examination of some micrometeorological methods for measuring dry deposition. US. EPA Report EPA-6C0/7-78-116. Hicks B. B. and Wesely M. L. (1980) Turbulent transfer processes to a surface and interaction with vegetation. In Atmospheric Sulfur Deposition (edited by Shriner D. S., Richmond C. R. and Lindberg S. E.), pp. 199207. Ann Arbor Press, Ann Arbor, MI Hicks B. B., We&y M. L. and Durham J. L. (1980) Critique of methods to measure dry deposition: Workshop summary. U.S. Environmental Sciences Research Laboratory, Research Triangle Park, NC.
Comparison of surrogate surface techniques for estimation of sulfate dry deposition Hicks B. B., Wesely M. L., Durham 1. L. and Brown M. A. (1982) Some direct measurements of atmospheric sulfur fluxes over a pine plantation. Atmospheric Environment 16, 2899-2903. Hicks B. B. (1983) Dry deposition processes. The acidic deposition phenomenon and its effects, A-7. EPA-600/883-016A (Draft). Hosker R. P., Jr. and Lindberg S. E. (1982) Review: atmospheric deposition and plant assimilation of gases and particles. hospheric E&ronment 16, 88%910: Lindbera S. E.. Harriss R. C.. Turner R. R.. Shriner D. S. and Huff b. D. (1979) Mechanisms and rates of atmospheric deposition of selected trace elements and sulfate to a deciduous forest watershed. Oak Ridge National Laboratory Report ORNL/TM-6674. Lindberg S. E. and Harriss R. C. (1981) The role of atmospheric deposition in an eastern U.S. deciduous forest. Wat. Air Soil Pollut. 16, 13-31. Little P. (1977) Dewsition of 2.75.5.0 and 8.5 urn Darticles to plant and s&l s&faces. Enuir. Pollut. 12, 243-jO5. McCall J. G. and Bush D. S. (1978) Precioitation and throughfall chemistry in the Sah F&cisco’Bay area. J. Enoir. Qual. 7, 352-357.
Munn R. E. and Bolin B. (1971) Review: global air pollutionmeteorological aspects. Atmospheric Environment 5, 363-402.
Nihlgard B. (1970) Precipitation, its chemical composition
635
and effect on soil water in a beech and spruce. forest in south Sweden. Oikos 21, 208-217. NOAA (1981, 1982) National Oceanic and Atmospheric Administration. Environmental Data and Information Service, National Climatic Center, Asheville, NC. Local Climatological Data, Monthly Summary for RaleighDurham Airport, NC. Raynor G. S., Hayes J. V. and Ogden E. C. (1974) Particulate dispersion into and within a forest. Boundary-Layer Met. 7, 429-456.
Sandberg J. S., Levaggi D. A., DeMandel R. E. and Siu W. (1976)Sulfate and nitrate oarticulates as related to SO, and NOI ‘gases and emissions. J. Air Polk. Control As;. 26, 559-564.
Schlesinger W. and Reiners W. (1974) Deposition of water and cations on artificial foliar collectors in fir-krummhoiz of New England Mountains. Ecology 55,378-386. Sehmel G. A. (1980) Particle and gas dry deposition: a review. Atmospheric Environment 14,983-1011. Wesely M. L. and Hicks B. B. (1979) Dry deposition and emission of small particles at the surface of the earth. hoc. Fourth
Symp. on Turbulence,
Dijiiion
and Air Quality.
Reno, NV, 15-18 January. Am. Met. Sot., Boston, MA, pp. 510-513. Wesely M. L., Cook D. R. and Hart R. L. (1985)Fluxes of gases and particles above a deciduous forest in wintertime. Boundary-Layer Met. (in press).