United States Environmental Protection Agency Atmospheric Sciences Research Laboratory Research Triangle Park NC 27711 Research and Development EPA/600/S3-86/037 Sept. 1986 SEPA Project Summary A Dry Deposition Module for Regional Acid Deposition C. M. Sheih, M. L. Wesely, and C. J. Walcek Methods to compute surface dry dep- osition velocities for sulfur dioxide, sul- fate, ozone, NO plus NO2, and nitric acid vapor over much of the North American continent have been developed for use with atmospheric numerical models of long-range transport and deposition. The resulting dry deposition module, actually a FORTRAN subroutine and a landuse map, has been designed for use with Eulerian models but can also pro- duce maps and averages of deposition velocities for other types of models. The module provides much of the data required to compute deposition veloc- ities: a computerized landuse map, sur- face roughnesses keyed to landuse type and season, and similarly keyed surface resistances of pollutant uptake. The landuse map has basic grid cells with dimensions of 1/4 degree longi- tude by 1/6 degree latitude, over the re- gion from 52 to 134 degrees west longi- tude and 24 to 55 degrees north latitude. External input data must specify geographical location, season, and height at which deposition velocity estimates are to be made, as well as provide values of atmospheric parame- ters such as solar irradiation, wind speed, atmospheric stability, and boundary-layer mixing height. These parameters are usually average values for gridded areas defined by the Eule- rian model. A fairly general dry deposi- tion module has been produced as well as a module adapted specifically for the Regional Acid Deposition Model being developed at the National Center for At- mospheric Research. This Project Summary was devel- oped by EPA's Atmospheric Sciences Research Laboratory, Research Triangle Park, NC, to announce key findings of the research project that is fully docu- mented in a separate report of the same title (see Project Report ordering infor- mation at back). Introduction Dry deposition results in substantial removal of trace substances from the atmosphere and accounts for a large portion of the sulfur and nitrogen com- pounds delivered to the surface. Atmos- pheric numerical models of long-range transport and deposition of such sub- stances must take into account dry dep- osition. This is the case, for example, in Regional Acid Deposition Model (RADM) being developed by the Na- tional Center for Atmospheric Research for the National Acid Precipitation As- sessment Program. The rates of deposi- tion are obtained by the expedient of multiplying pollutant concentrations by deposition velocities. To improve esti- mation of the deposition velocities, it is necessary to incorporate the latest re- search findings and compile the neces- sary formulae and data. For RADM, the results of such work are applied in the form of a dry deposition module, which includes a FORTRAN subroutine and a landuse map for the continental United States and its surrounding regions. In addition to sulfur dioxide and sulfate particles addressed in earlier efforts, 03, NO plus NO2, and NH03 are included in the present study. Many variables control the dry depo- sition velocities of airborne chemical substances. Each chemical species has distinct chemical and physical proper- ties that strongly affect uptake at the surface. Correspondingly, each type of surface has its own influential set of physical, chemical, and biological char- ------- acteristics. Indeed, deposition velocities vary widely depending on chemical species, surface type, season, and time of day. For a region as large as the con- tiguous United States and surrounding areas in Canada, Mexico, and bordering seas, development of an appropriate dry deposition module requires some balance between identification of the details of processes that control dry deposition and the computational time available to estimate deposition veloc- ities over large areas in small time steps. In the present study, we address a simplified scheme to compute dry deposition velocities averaged over sur- face grids with typical side dimensions of tens and kilometers. Considerable generalization of results from research on dry deposition is made in order to achieve a working dry deposition module. Procedures The deposition velocity vg for a gas at height z over land is computed as vg = ku.[ln(z/z0) + 2(Dh/DgP3 + ku.rg - i|»cr1 , (1) where k is the von Karman constant, u, is the friction velocity, z0 is the surface roughness scale length, Dh and Dg are the molecular diffusivities for heat and the gas of interest, respectively, <|ic is the stability correction function for the gas, rg is the surface resistance to uptake of the gas. The deposition velocities of sul- fate particles over water and land are computed from vp = ku.[ln(z/z0) + ku.rp (2) where rp is the surface resistance for particle uptake. To determine deposition velocities with these equations, the parameters that must be specified are surface roughess, molecular diffusivity, stability correction function, friction velocity, and surface resistance. Molecular diffu- sivities are provided within the module, while friction velocity and atmospheric stability are input variables. The surface roughnesses and the surface resis- tances for SO2 and 03 are provided by lookup tables that specify landuse types and seasonal categories. The landuse types are classified as follows: 1. urban land, 2. agriculture land, 3. range land, 4. deciduous forest, 5. coniferous forest, 6. mixed forest including wetland, 7. water, 8. barren land, 9. non-forested wetland, A. mixed agricultural and range land, and B. rocky open areas occupied by low growing shrubs. The seasonal categories are: 1. midsummer, 2. autumn, 3. late autumn, 4. winter, and 5. transitional spring. The landuse data used in the present study cover an area from 52 to 134 de- grees west longitude and 24 to 55 de- grees north latitude. The area is divided into a matrix of 328 x 186 (longitude by latitude) grid cells with increments of 1/4 and 1/6 degree longitude and lati- tude, respectively. Data for each grid cell contain longitude and latitude coor- dinates of the cell and the percentages of the areas used by the 11 landuse types in the cell. A sample landuse map of the most prevalent landuse type in each one-degree square is shown in Fig- ure 1. The surface resistance tables for S02 and 03 contain values partitioned ac- cording to solar irradiation during the daytime in order to account for the influ- ence of variations of vegetational stom- atal openings on surface uptake. A spe- cial category is added at night for very light winds when dew is likely to form on the surface. For NO plus N02, the surface resistances are computed on the basis of 03 surface resistance cou- pled with selected algorithms. The sim- plest species to deal with is HN03 be- cause the surface resistance is assumed to be 0.1 s cm"1 in all cases. For sulfate particles, the surface resistance tables are not used. Instead, equations provide the surface resistance as a function of friction velocity, atmospheric stability, and boundary-layer inversion height, with only a minimal dependance on sur- face roughness. Parameters of input to the module must include chemical species, height at which deposition velocity is needed, friction velocity, Monin-Obukhov length (i.e., atmospheric stability), solar irradi- ation, atmospheric temperature, boundary-layer inversion height, and air temperature and humidity. iSSSSSSSS iSSSSSSS! >56666669( t\ iSSSSSSSS 5956222* 56666666 £79996: 7SSSSSS5 .55555' '6555! 777777777! 555S3293! 777777777; 5X355265 777777777; 5SS33S: S! 7777777777555533: 333323S3333: 7777777771553533303333: 33333: 777777777; 355! 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'77/777777777777/77777 '777777777 7777777777777777777777? 7777777777777 777777777777777777777773 7777777777777777777777777? 777777777777777777777777777 77777777777777777777777777777 7777777777777777777777777777? 7777/777/777777/777///7777T? !777777777777777777777777777? 7777777777777777777777777? 7777777777777777777777777? l7777//77/777777777///777777? Figure 1. A landuse map of North America with locally dominant landuse types representei by alphanumeric symbols. ------- Results and Discussion Sample maps of dry deposition veloc- ities of nitric acid vapor and sulfate par- ticles are shown in Figures 2 and 3. These assume summer daytime condi- tions when solar irradiation levels are greater than 400 W m~2 and wind speeds are moderate, corresponding to approximately 3.8 m s~1 at a height of 10 m above a surface with z0 equal to 3 cm. A sensible heat flux of 150 W m"2 is assumed over all land surfaces and 20 W m"2 is assumed for water sur- faces. Nitric acid vapor and sulfate parti- cles are chosen for illustration because they have extremes in deposition veloc- ity. At heights of 10 m above the north- eastern United States during daytime summer conditions, for example, the average deposition velocity values are near 3.5 cm s~1 for HN03 DUt are an order of magnitude less for paniculate sulfur. At night, values of deposition ve- locity for paniculate sulfur, are typically smaller than 0.05 cm s~1 (not shown). RADM has successfully utilized the dry deposition module to compute dep- osition of S02, S04~, and HNO3 over the eastern United States for three rainy days in the springtime. Domain aver- aged midday deposition velocities were found to be 0.8 cm s~1 for S02, 0.2 cm s"1 for sulfate, and 2.5 cm s"1 for HN03. Most Eulerian models provide sets of atmospheric parameters that are meant to be averages over entire grid cells. For example, the mesoscale meteorology model of RADM gives one average pro- file of wind speed, temperature, and hu- midity per grid square of 80 by 80 km. From the profiles, the fluxes of momen- tum, heat, and moisture required for in- put to the dry deposition module must be derived in order to compute deposi- tion velocities via Equations. (1) and (2). In the current version of the module used in RADM, grid-averaged fluxes are derived from the profiles with semiem- pirical equations designed to avoid time-consuming iterative calculations necessary with conventional microme- teorological formulae. For each grid cell in RADM, a new av- erage friction velocity is estimated on 4' 5555446! 1241 434< 13444354 12541 • J3343444 4S4SSSSS4SIIII lilt 11111 Itlltll UI1I1U1 UlllUII IIIIUIU tT^cav 1333344 44 UltlltU Utlltlll 533341 1444*444 546! >2332i 2S43- 54S633? 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The integers (0, 1, ---, and9)inthe map represent deposition velocities with intervals of 0.596 cm s"1; e.g., 0 and 1 represent the ranges of deposition velocities 0 to 0.596 and 0.596 to 1.192 cm s~\ respectively. the basis of a grid-averaged wind speed and a surface roughness computed as the logarithmic average of values weighted by the fraction of area covered by each landuse type. The products of wind speed and friction velocity are then assumed constant over all surfaces within the grid, at a specified height near 40 m. This allows computation of the local friction velocity and wind speed above each landuse type, via the equation of the logarithmic wind profile and the surface roughness for each landuse type. This provides both realis- tic variations in local friction velocity above each grid cell and a distribution of wind speed that, when averaged, is consistent with the grid-averaged wind taken from RADM. The heat and mois- ture fluxes important in computing the Monin-Obukhov length are assumed constant and equal to the grid averages, which is a deficiency, but a small one compared to the practice of assuming constant friction velocity, or alterna- tively, wind velocity. Conclusions The dry deposition module provides a means of computing surface dry depo- sition velocities of major chemical com- pounds for numerical modeling of acid deposition. The subroutine will produce deposition velocities for S02, SO^, 03, NO plus NOX, and HN03 at each grid cell with dimension of 1/4 degree longitude by 1/6 degree latitude, for the continen- tal United States and surrounding regions. It should be noted that insuffi- cient information on surface resistances necessarily limits the accuracy of the computed deposition velocities. Current knowledge of the resistances is good for SO2, HN03 and 03, fair for SO4=, and poor for NO and NO2. However, the sub- routine can be easily updated to include new results of research or modified to include additional chemical species. The dry deposition module is quite easy to apply as provided. The multiple factors that control surface resistances for a given chemical substance over a specified type of surface are taken into account, but not explicitly, so that calcu- lations of deposition velocity can be made very efficiently. A drawback of this approach is that considerable work, often of a research nature, is necessary to modify the module to include addi- tional chemical species. Other deficien- cies of the module include ignoring such factors as rapid in-air chemical re- actions, which can change the deposi- tion velocity with height, and the effects ------- 9899999S 599999999!99776997(597887 9999999S399998899! 9999999S 14729889 23122799999999909998889!98998999 I497 999! 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A dry deposition velocity map of paniculate sulfur with deposition velocity intervals of 0.0412 cm s"1 of nonuniform and hilly terrain. Also, the temporal variations of surface resis- tance caused by the surface being wetted by dew or rain are not addressed explicitly in the module, and thus must be taken into account by other compo- nents of the controlling numerical model. C. M. SheihandM. L Weselyare with Argonne NationalLaboratory, Argonne, IL 60439; C. J. Walcek is with the National Center for Atmospheric Research, Boulder, CO 80307. Jason K. S. Ching is the EPA Project Officer (see below). The complete report, entitled "A Dry Deposition Module for Regional Acid Deposition," {Order No. PB86-218 104/A S; Cost: $11.95, 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: Atmospheric Sciences Research Laboratory U.S. Environmental Protection Agency Research Triangle Park, NC 27711 ------- |