United States
Environmental Protection
Agency
Environmental Monitoring
Systems Laboratory
Research Triangle Park NC 27711
Research and Development
EPA/600/S4-88/027 Sept. 1988
Project  Summary
Comparison of the  RADM  Dry
Deposition  Module with  Site -
Specific Routines for Inferring
Dry  Deposition
M. L. Wesely and B. M. Lesht
  The computer module for calculating
dry deposition velocities in the Regional
Acid Deposition Model (RADM) has been
modified to operate with site-specific
data provided by measurement stations
such as CORE (COre Research Establish-
ment, for dry deposition) satellite sites.
Data collected during 1986 at seven
widely separated sites  in the eastern
United States were used to estimate
weekly averages of deposition velocities
for SO2, 03, HN03, and S042'. Similar
calculations were made with the inferen-
tial technique that was developed at At-
mospheric Turbulence  and Diffusion
Division of the National Oceanic and At-
mospheric Administration's  Air Re-
sources  Laboratory. Comparison  of
results obtained with the two techniques
indicate  that  some systematic dif-
ferences exist, even when the module
uses distributions of landuse types that
match as closely as possible the observ-
ed vegitation coverages used in the in-
ferential technique. When one ignores
the systematic differences that could be
removed  by  minor changes  in the
algorithms for computing resistances to
deposition, the relative uncertainties for
S02and O3 deposition velocities are ap-
proximately 30%. Likewise, the relative
uncertainties  corresponding  to  non-
systematic differences in the deposition
velocities for HN03 and SO42' are about
30% and 50%, respectively. Use of
the landuse map to extrapolate to areas
as large as RADM qrid cells (approx-
imately  8O  km square)  around the
measurement sites produces weekly
averages of deposition velocities for
SO2, O3,  and SO42' that  are within
20% of those computed for the local
site and approximately 30% for HNO3,
if one avoids landuse types such as ur-
ban  and  water  areas  that are
nonrepresentatlve  and  have very dif-
ferent characteristics from the measure-
ment sites.  These estimates  do not
represent true uncertainty or accuracy
because of unknown sources of error
possible in the input data and deposition
velocity algorithms for nonuniform
surfaces.
  This Project Summary was developed
by  EPA's Environmental  Monitoring
Systems Laboratory, Research Triangle
Park, NC, to announce key findings of the
research project that is fully documented
in a separate report of the same title (see
Project Report ordering information  at
back).

Introduction
    The dry  deposition  module  of  the
Regional Acid Deposition Model (RADM) is
used to compute  the  dry deposition
velocities (downward flux divided by con-
centration at a specified  height) for SO2,
SO42', O3, HNO3, and other compounds.
With its computerized landuse map, the
module can  provide estimates of the
deposition velocities for  a given set  of
meteorological and surface conditions that
are representative  of an area  located
anywhere in the contiguous United States
and nearby locations. As  part of this proj-
ect, the module uas been modified to ac-
cept data on  meteorological and surface
conditions observed at measurement sta-
tions rather than inputs  computed with

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RADM. The purpose of these modifications
was to make site-specific estimates of dry
deposition velocities, and compare them
with results from the site-specific inferen-
tial technique that has been developed at
the Atmospheric Turbulence and Diffusion
Division (ATDD) of NOAA's Air Resources
Laboratory. Goals of the comparisons in-
clude estimating the relative uncertainties
of the two techniques, suggesting  im-
provements, and examining the ability of
the modified module to  provide estimates
of dry  deposition  for  expanded  areas
around the measurement sites.
  The observational data  used in these
analyses  were  collected  with  ATDD in-
struments during 1986 at the seven sites
listed in Table  1. The sites identified  are
either CORE (COre Research  Establish-
ment, for dry deposition) stations or CORE
satellite stations. The data set itself consists
of hourly averages of  wind speed,  the
standard deviation  of the horizontal wind
direction, solar irradiation, air temperature,
relative humidity, and surface wetness from
a sensor  that indicates the presence of
moisture from dewfall and rainfall. Other
data include one observation per week of
the fraction of full leaf cover, from which the
seasonal categories used in the module are
derived, and the information given in Table
          1  describing the types  and amounts of
          vegetative species present at the local site.
          The landuse distributions for the local site
          are determined from the relative amounts
          of these species, while the distributions for
          the RADM grid squares (approximately 80
          km square) encompassing each site are
          derived  entirely  from the  computerized
          RADM landuse map. Although the deposi-
          tion velocities (vd) are computed for every
          hour, the results  considered here are
          averages over periods of at least one week.

          Results and Conclustions
            The dry deposition module of the RDAM
          has been successfully adapted to use site-
          specific data obtained at dry deposition sta-
          tions such as the CORE satellite sites. The
          module was originally written to use more
          complete local micrometeorological  infor-
          mation  than is included in the parameters
          listed above, so considerable manipulation
          of the coding was needed in the RADM
          module in order to accept these inputs.
          Perhaps the least exact formaulations  in the
          modified module are those that deal with
          estimating atmospheric stability, but uncer-
          tainties  introduced by the compromised
          equations are probably overshadowed by
          the fact that most of the sites are located
          in areas with surface properties insufficient-
   ly uniform, or with terrain insufficiently flat,
   to allow very precise micrometeorological
   calculations. The algorithms in the modified
   module that are used  to compute crucial
   parameters such as aerodynamic resist-
   ance above the surface and friction veloci-
   ty are quite similar to those used in the in-
   ferential  technique.  Some notable differ-
   ences exist, however. One is that the modi-
   fied module attempts to mimic the RADM
   module by computing changes in the gas-
   phase resistances for surfaces identified by
   landuse types different from the dominant
   landuse type for the local site. At most of
   the sites, this alteration produces smaller
   aerodynamic resistances and larger friction
   velocities averaged over the areas sur-
   rounding the site, and thus increases the
   deposition velocities for HNO3. The deposi-
   tion velocities for other substances do not
   seem to be significantly affected, because
   their surface resistances are usually much
   larger  than the  aerodynamic and gas-
   phase sublayer resistances (which depend
   on friction velocity).
     The alogrithms used in the modified
   module to compute the bulk surface resist-
   ance, usually the most important term for
   determining deposition velocities, are the
   same as  those used in  the RADM module.
   Some  changes  had to be made  in the
Table 1.    Site names, locations, predominant surface vegetation (within one kilometer), and landuse types assumed with the modified module
General Location
(deg lat., long.)
               Site
               ID
  Local Surface Vegetation and Landuse Types*
             (percent coverage)
Argonne National
Laboratory, IL
41.TON, 87.98 W)

Bondville
(Champaign), IL
(40.05 N, 88.37 W)

Oak Ridge, TN
(35.96 N, 84.28 W)
Panola State
Park, GA
(33.63 N, 84.18 W)

Pennsylvania
State Univ., PA
(40.72 N, 77.92 W)

West Point, NY
(41.35 N, 74.05 W)
Whiteface
Mountain, NY
(44.39 N, 73.86 W)
                                                ARG
              BON
              OAK
                                                PAN
               PSU
               WST
                                                WHT
grass (SO), white oak (SO)
local site: 2(50), 4(50)
RADM square: 1(23), 2(62), 4(2),  7(13)

maize (50), soybeans (50)
local site: 2(100)
RADM square: 1(2), 2(98)

white oak (70), loblolly pine (30)
local site: 4(70), 5(30)
RADM square: 1(3), 2(30), 4(64),  7(3)

Loblolly pine (50), chestnut and red oak (50)
local site: 4(50), 5(50)
RADM square: 1(13), 2(22), 4(28), 5(6), 6(29),  7(2)

maize (30), white oak (30)
local site: 2(50), 4(50)
RADM square: 1(4), 2(20), 4(73),  5(3)

maple (60), white oak (30)
local site: 4(100)
RADM square: 1(41), 2(3), 4(28),  6(2), 7(26)

white birch (70), maple (10)
local site: 4(100)
RADM square: 1(1), 2(6), 4(28), 5(10), 6(43), 7(12)
'Landuse types specified are [1] urban land
 fresh water.
[2] agricultural land, [4] deciduous forest, [5] coniferous forest, [6] mixed forest including wetland, and [7] water, both salt and

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 parameterizations  of the  SO<2 sublayer
 resistance in air, which strongly controls
 SO42" deposition velocity, but the changes
 conform with the interpretation of the field
 experiments on which the parameteriza-
 tions are based. The inferential technique
 is configured somewhat differently and ap-
 pears to overestimate the deposition veloci-
 ty for SO42- in some situations. The mod-
 ule, however, tends to underestimate when
 the standard deviation of the  horizontal
 wind direction is not measured very well.
  The most striking difference between the
 results  of the module  and the inferential
 technique is the much smaller estimates
 made with inferential technique for SO2 and
 03 deposition velocities during nonsummer
 conditions. These  are probably underesti-
 mates caused by overly restrictive assump-
 tions on the surface resistances of bare soil
 and sparse vegetation during nonsummer
 seasons, which could easily be  adjusted by
 changing the values of a few numerical
 coefficients  used  in the  inferential
 technique.
  While the algorithms  for  surface
 resistance in the modified module are bas-
 ed on a more complex and versatile set of
 multiple surface resistances to various por-
 tions of the surface than the algorithms us-
 ed in the current version of the inferential
 technique, the module is strongly limited by
 the fact that the surface can be described
 by at most 11 landuse types. The inferen-
 tial  technique employs  description of
 vegetation by species and tailors the sur-
 face resistances more  precisely than the
 module to describe the physiological re-
 sponses to environmental parameters such
 as solar irradiation and temperature. An ad-
 ditional  feature that may be desirable is a
 factor to take into account soil moisture
 stress  on  the stomatal  resistances of
 healthy  vegetation during the  daytime,
 because the current version of the inferen-
 tial  technique assumes no soil moisture
 stress and the module is effectively tuned
 to a small amount of moisture stress. As a
 result,  the  deposition  velocities  of
 substances such as SO2 and O3 that are
 strongly influenced by stomatal resistances
 are slightly larger when computed by the
 inferential technique than with the modified
 module.
  For the weekly averages of  deposition
velocities computed for 1986 at the seven
sites,  the inferential technique  and the
 modified module produce estimates within
about 3O% of each other for SO2 and O3,
if we neglect strong systematic differences
such as those that occur during nonsum-
mer conditions at surfaces with bare soil
or sparse vegetative canopies. Likewise,
 the  differences for HNO3 and SO42'
 deposition velocities are usually about
 30%  and  50%, respectively.  These
 relative uncertainties could probably be
 reduced somewhat if the suggestions made
 above were adopted.
   Estimates of deposition velocities over
 large areas are easily computed with the
 modified module by use of the appropriate
 landuse distributions.  Of course, if the
 areas are very large, the observations of
 meteorological conditions at the measure-
 ment stations  might not  be sufficiently
 representative. Some trial runs involving the
 20-km squares of the landuse map cell and
 the  80-km  RADM  cells  at the  seven
 measurement sites show that the estimates
 of weekly averaged deposition velocities for
 SO2 ,O3 and SO42' are fairly sensitive  to
 the amounts of urban and water areas in-
 cluded in landuse distributions. Aside from
 this  effect,  the  deposition  velocities
 caiculated for these three substances over
 the  RADM grid cells are usually within
 20% of those for the local site descrip-
 tions. These limits should not be taken as
 generally valid at sites other than the seven
 examined in this study, because different
 meteorological conditions and altered com-
 binations of landuse types  could cause
 larger changes in deposition velocities. For
 HNO3, minor changes in the assumed lan-
 duse distributions often cause rather large
 changes,  easily  30%,  in deposition
 velocities.
  We conclude that the  differences  in
deposition  velocity estimates caused by
scaling from local site conditions to RADM
grid cells are often slightly smaller than the
relative  uncertainties of the deposition
velocities  estimated with  the  modified
module  and  the  inferential technique.
Hence, inferences of deposition velocities
for the local conditions at carefully chosen
sites appear to be reasonably represen-
tative of larger areas extending at least to
sizes of RADM grid squares. Nevertheless,
adjustments for changes in surface condi-
tions are clearly desirable, and extrapola-
tion to types of surfaces that have notably
different properties can be made only at the
cost of considerably greater uncertainty. By
use of a computerized landuse map or,
preferably, a more detailed description of
surface conditions, one should be able to
estimate weekly averaged dry deposition
amounts for sulfur, nitric acid, and ozone
to within about  30% over some fairly
large areas.
  The above number of 30% is not the true
uncertainty or accuracy. An assessment of
accuracy would  require   experiments
designed specifically for dry deposition,
because a number of factors can cause ad-
ditional uncertainty. For example, one must
determine  how  representative the  local
meteorological measurements actually are.
Relatively low wind speeds measured at
OAK  and PAN suggest  that proper ex-
posure of instruments in  a forested,  hilly
area  might  be  difficult. In  addition,
measurements taken at sites not represen-
tative of any one surface or influenced by
local aerodynamic obstacles might not be
suitable for application of the algorithms
used in the inferential and the module ap-
proaches. Finally, these algorithms do not
directly consider the  effects of surface
nonuniformities in the area considered, in-
cluding hills, isolated surface irregularities,
and  edges associated with changes in
height of surface cover. The aerodynamic
resistances could be strongly altered by
surface nonuniformities, and stomatal re-
sistances  could   be altered  by varying
degrees of shading of sunlight by hills and
other vegetation.

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     M. L Wesely and B. M. Lesht are with Argonne National Laboratory, Argonne,
       IL 60439.
     Steven M. Bromberg is the EPA Project Officer (see below).
     The complete report, entitled "Comparison of the RADM Dry Deposition Module
       with Site-Specific Routines for Inferring Dry Deposition," (Order No. PB 88-
       238 191/AS; Cost: $19.95, subject to change) will be available only from:
             National Technical Information Service
             5285 Port Royal Road
             Springfield, VA 22161
             Telephone: 703-487-4650
     The EPA Project Officer can be contacted at:
             Environmental Monitoring Systems Research Laboratory
             U.S. Environmental Protection Agency
             Research Triangle Park, NC 27711
United States
Environmental Protection
Agency
Center for Environmental Research
Information
Cincinnati OH 45268
Official Business
Penalty for Private Use $300
EPA/600/S4-88/027
            0000329
                                             AGENCY

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