United States Environmental Protection Agency Atmospheric Sciences Research Laboratory Research Triangle Park NC 27711 Research and Development EPA/600/S8-85/016 Sept. 1985 SEPA Project Summary User's Guide for the Advanced Statistical Trajectory Regional Air Pollution (ASTRAP) Model Jack D. Shannon The Advanced Statistical Trajectory Regional Air Pollution (ASTRAP) model simulates long-range, long-term trans- port and deposition of air pollutants, primarily oxides of sulfur and nitrogen. The ASTRAP model is designed to com- bine ease of exercise with an appropri- ate detail of physical processes for as- sessment applications related to acid deposition. The theoretical basis and computational structure of the ASTRAP model are described. Major simplifica- tions and assumptions incorporated in the model are discussed. The data requirements for ASTRAP simulations are monthly to seasonal time series of transport wind and pre- cipitation analyses and an emissions in- ventory. ASTRAP consists of three pro- grams: HORZ, VERT and CONCDEP. The source code is in standard FOR- TRAN, while the JCL is appropriate for an IBM 3033 mainframe computer. Horizontal dispersion and wet deposi- tion statistics are calculated in HORZ. The process of turbulent vertical dif- fusion within the mixed layer, leakage to the free atmosphere, chemical trans- formation and dry deposition are calc- ulated in VERT. The CONCDEP pro- gram combines the statistics produced by HORZ and VERT with an emissions inventory to calculate primary and secondary pollutant surface concen- trations along with wet and dry dep- ositions. This Project Summary was devel- oped by EPA's Atmospheric Sciences Research Laboratory, Research Triangle P-rk, 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 The Advanced Statistical Trajectory Regional Air Pollution (ASTRAP) model described here has been developed to simulate the long-term (monthly to yearly), regional-scale (resolution about 100 km) deposition of oxides of sulfur and nitrogen, the major contributors to acid deposition. The ASTRAP tech- niques can be extended to other pollu- tants, provided that linear parameteriza- tions of chemical transformation and removal processes are suitable. They also can be extended to other spatial scales, if appropriate meteorological data are available. Unmodified exten- sion of the modeling techniques used in ASTRAP to shorter, episodic temporal scales is not recommended because of certain statistical features of the model. The ASTRAP model consists of three submodels and various preprocessors and postprocessors. Use of particular preprocessors and postprocessors de- pends on application and data availabil- ity. The submodels are the vertical diffu- sion program (VERT), the horizontal dispersion program (HORZ), and the concentration and deposition program (CONCDEP). The processes of vertical diffusion, chemical transformation, and dry deposition are simulated in VERT through parameterizations that are in- dependent of horizontal location or par- ticular meteorological conditions. In HORZ, the processes of horizontal ad- vection, horizontal diffusion, and wet deposition are simulated through the ------- use of time series of wind and precipita- tion analyses. The CONCDEP program combines the statistics produced by the first two programs with emission inven- tories to produce fields of average at- mospheric concentration and cumula- tive deposition. The ASTRAP model can be applied in emission policy assessments, for which the model can be exercised to predict how deposition fields would change in response to changes in the pollutant emission field. Assuming linearity be- tween emissions and deposition, the model can be used to estimate concen- tration and deposition at specific recep- tor locations, and it can estimate the in- dividual contribution from different sources or source regions. The follow- ing major simplifications and assump- tions have been incorporated into the ASTRAP model: 1. Long-term horizontal and vertical dispersion can be simulated inde- pendently. 2. Long-term horizontal diffusion can be approximated by the spread of plume centerlines; small-scale diffu- sion about individual plumes is ignored. 3. Chemical transformation can be parameterized as a linear, first-order process. 4. Wet removal is a function of the half- power of the precipitation. 5. Transport is two-dimensional. 6. The dry deposition parameterization is horizontally uniform. The data requirements for ASTRAP simulations are monthly to seasonal time series of transport wind and pre- cipitation analyses and an emissions source inventory. Initial preparation of wind and precipitation fields for AS- TRAP simulations has been performed at the University of Michigan by Perry Samson. His initial wind fields, pro- duced every 12 h are for 500-m layers upto3000-m MSLfora 17 x 19 horizon- tal grid of National Meteorological Cen- ter (NMC) spacing. Speed is given in meters per second. Linear temporal in- terpolation has created fields at 6-h in- tervals, and the wind analyses have been combined into three-month-long files (December-February, March- May, June-August, and September- November). The wind components have been internally converted to com- ponents along the NMC axes in the HORZ subprogram. The precipitation analyses produced at the University of Michigan are on a 50 x 45 grid with 1/3 NMC spacing. The original analyses are hourly; there is a special code for missing data. Precipita- tion amount is given in millimeters. The hourly fields have been added to pro- duce six hourly fields; the missing data were filled by interpolation and extrapo- lation. The precipitation data are ar- ranged on monthly files. An S02 inventory has been created in which the seasonal emissions in kilo- tonnes are given by effective stack layer and NMC position of the lower left cor- ner of the grid cell. No separate SO| emissions inventory is used, so primary sulfate emission factors are applied in CONCDEP. The primary sulfate emis- sion factor for sources in the lowest layer (0-100 m) is assumed to be 0.05 (i.e., one unit of SO2 equivalent emis- sion is treated as 0.95 units of S02 and 1.5 (0.05) = 0.075 units of primary sul- fate; the 1.5 factor arises because the ratio of the molecular weight of sulfate to that of S02 is 96/64). The primary sul- fate emission factor for point sources is assumed to be 0.03 in Florida and the northeast and 0.015 elsewhere. The emission grid has the same spacing as the precipitation grid, but it is irregular because the inventory is arranged by state and province. The emission infor- mation has been derived from a prelim- inary version of the National Acid Pre- cipitation Assessment Program (NAPAP) inventory for 1980. Wind, pre- cipitation, and emission data are all written in binary format for efficiency. Technical Description Horizontal dispersion statistics are calculated in HORZ for a virtual source grid covering the contiguous United States and Canada for a particular mete- orological period and are subsequently interpolated when concentrations and depositions are calculated. For a one- to-three-month sequence of meteoro- logical analyses, simulated tracers of unit mass are released from the sources at 6-h intervals. Calculations in HORZ are independent of the height of re- lease. The tracers are tracked for 28 time steps (seven days) or until they leave the wind grid. At each successive tracer position, the precipitation field is checked to see whether there should be wet removal. The statistics calculated in HORZ are ensemble statistics; each ensemble rep- resents all trajectory positions of a par- ticular plume age for each source for the length of the meteorological analysis. The statistics generated for a puff de- scribing the density of the ensemble of equal age trajectory end points are the coordinates p.xand jxy of the mean posi- tion, the standard deviations ax and cry, the correlation term pxy, and n, the num- ber of equivalent tracer masses con- tributing to the ensemble statistic. The statistics are collected for a puff associ- ated with airborne or dry tracers and for another puff associated with wet depo- sition tracers. The wet deposition is parameterized as a function of the half-power of the precipitation. It contains certain con- straints such that any precipitation amount larger than 1 cm/6h has the same effect as that of 1 cm/6h, while precipitation amounts less than a mini- mum threshold value of 1 mm/6h have no removal effect at all. As previously mentioned, there are separate sets of statistics for wet and dry tracer ensembles. The same trajec- tory end points are used in calculation of each corresponding pair of wet and dry ensembles, but the weights are dif- ferent (most of the wet ensembles have zero weight) and, thus, the wet and dry ensemble puffs differ. The puffs for dry deposition and surface concentration tend to be more regular in the trend of their overlapping positions than do the wet deposition puffs. This is because wet deposition is a highly irregular pro- cess and thus exhibits more statistical variation for a single season. The process of turbulent vertical dif- fusion in the mixed layer, leakage to the free atmosphere, chemical transforma- tion, and dry deposition are calculated in the VERT program. The diurnal varia- tion of the planetary boundary layer is parameterized in VERT through a sea- sonally and diurnally varying stability profile .(vertical eddy diffusjvity speci- fied for each layer of the model). The variations in dry deposition amounts associated with typical diurnal and seasonal patterns of both atmos- pheric stability and surface resistances are parameterized through average di- urnal values of dry deposition velocities for each season. A diurnal variation in the linear first-order transformation rate of the primary pollutant (S02 or NO/ N02) to a secondary pollutant (SOJ or N03) directly or indirectly due to photo- chemical activity patterns is also com- pensated for in VERT. The seasonal pat- terns are intended to include all chemical transformation pathways ex- cept those associated with precipitating clouds. The rates of S02 transformation, for example, are greater than those nor- ------- mally found in clear-air experiments, because the rates include the effects of chemical processing in nonprecipitating clouds. Leakage from the mixed layer into the free atmosphere is now parameterized in ASTRAP, but the rates have been set at relatively low values until more is learned about the long-term regional significance of the layer. The calculated and stored normalized statistics from the VERT program for a seasonal simulation include the one- dimensional surface concentration, the pollutant mass remaining aloft, and the pollutant mass deposited by dry pro- cesses during the time increment. Sepa- rate sets of statistics are maintained for S02, primary and secondary SOJ, as well as N0/N02, primary and secondary NO3. The eddy diffusivity, chemical transformation, and dry deposition parameterizations for a particular sea- son are applied everywhere, regardless of latitude or surface vegetation. This is an obvious limitation of the ASTRAP al- gorithms, which include some oversim- plifications to achieve computational simplicity and efficiency. The CONCDEP program combines the statistics produced by HORZ and VERT programs with an emissions inventory to calculate primary and secondary pol- lutant surface atmospheric concentra- tions and wet and dry depositions. The concentration and deposition fields are calculated by overlaying puffs and adding their densities over the receptor grid. For this, the puffs must be weighted by both the emissions rate per 6 h for the source and the number of normalized tracer masses contributing to the puff. Emissions from a hypothetical source in Oklahoma were combined with sum- mer vertical dispersion statistics and with trajectory statistics for June through August, 1980, to perform a sea- sonal simulation in a test of the model. Arrays of the concentration and deposi- tion fields and a table of total deposition for each receptor (state or province) were generated. Computer Aspects As currently structured, ASTRAP con- sists of three programs: HORZ, VERT, and CONCDEP. The job control lan- guage is appropriate for the IBM 3033 mainframe computer at the Argonne National Laboratory; it would require some modification for use on other sys- tems. While programming is in stand- ard FORTRAN, input and output algorithms may require coding modifi- cation for other systems. On an IBM 3033, VERT requires 210k (bytes) stor- age, 5-10 min of CPU time, and one output file for a seasonal simulation. HORZ requires 500k storage, 10 min CPU time, two input tape drives, and an output file for a seasonal simulation. CONCDEP requires 500k storage, 10-15 min CPU time, an emission input file, the output files from the other two sub- programs, a file used to identify each receptor cell as a state or province, and an output file for a seasonal simulation. The output file from CONCDEP is nor- mally stored on disk, where postproces- sors can later be used to display the results graphically. Jack D. Shannon is with Environmental Research Division of Argonne National Laboratory. Argonne. IL 60439. Terry L. Clark and Jason K. S. Ching are the EPA Project Officers (see below). The complete report, entitled "User's Guide for the Advanced Statistical Trajectory Regional Air Pollution (ASTRAP) Model," (Order No. PB 85-236 784/AS; Cost: $11.50, 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 Officers can be contacted at: Atmospheric Sciences 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/S8-85/016 0000329 PS U S ENVIR PROTECTION AGENCY REGION 5 LIBRARY 230 S DfARBORN STREET CHICAGO IL 60«04 ------- |