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O 3. NO 3. OH. TICs. NO X. H 2 O. Modification to the chemistry algorithm in SCIPUFF. SCIPUFF Dispersion. df A. k A = max( k A sin( F ) , k A ). dt. (min). (max). = -k A f A. X T (x,y,t) = ∫ f A c(x,y,0,t) dt. t.

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Modeling Toxic Industrial Chemicals (TICs) and CWAs


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    1. O3 NO3 OH TICs NOX H2O Modification to the chemistry algorithm in SCIPUFF. SCIPUFF Dispersion dfA kA= max(kA sin(F), kA ) dt (min) (max) = -kA fA XT(x,y,t) = ∫ fA c(x,y,0,t) dt t kA= keff = f(F, T,cc, [amb], humidity, etc.) 0 Modeling Toxic Industrial Chemicals (TICs) and CWAs Using an Atmospheric Chemistry Module in SCIPUFF Douglas S. Burns, Veeradej Chynwat, Jeffrey J. Piotrowski, Kia Tavares, and Floyd L. Wiseman ENSCO, Inc., Melbourne, FL Run Photochemical Box Model (PBM) Background The goal of this DTRA sponsored project was to generate a set of polynomial functions that describe the atmospheric degradation rates for typical Toxic Industrial Compounds (TICs). Atmospheric degradation rates generally depend upon a variety of meteorological parameters such as the time of day, zenith angle, relative humidity, temperature, and ambient conditions. The largest rate processes for most organic species include the reactions with hydroxyl radical (OH), ozone (O3), and nitrate radical (NO3). Current atmospheric models, such as the Carbon Bond Mechanism (CBM), account for the reactions with these indigenous species, as well as reactions with other species, and often these models contain over a hundred chemical reactions and close to a hundred different chemical species. The computer code for generating the concentration profiles for the TICs/CWAs requires solving a large system of ordinary differential equations (ODEs), that is computationally intensive. The benefit of replacing this large set of ODEs with a set of polynomial functions is in saving both cpu and wall clock run time. The drawback is some loss of precision by using the simpler polynomials. ENSCO, Inc. has developed polynomial functions for describing the atmospheric degradation rate constants for a series of Alkenes (e.g., 1-butene and 2-methylpropene), H2S, and Sarin. The parameters in the polynomials are obtained by fitting the polynomials against model-generated data. The polynomials are then incorporated into the SCIPUFF T&D Model as part of an atmospheric chemistry module in HPAC. Tests were conducted to ensure that model run time is not affected by incorporating the chemistry module. 1-butene is fairly reactive, as are many other TICS, and so the effect of including a chemistry module will be to reduce the toxic footprint for a release of 1-butene. The methodology described here has been developed and can be readily applied to any atmospheric pollutant. Develop Chemical Data for TICs / CWAs TIC: Atmospheric Reactions of 1-butene or H2O NOX kOH kNO3 kO3 CH2=CHCH2CH3 + OH 0.94 C2H5CHO (1-butene) CH2=CHCH2CH3 + NO3  0.6 CH3CH2–CH(OH)—CH2ONO2 0.12 C2H5CHO + 0.11 H2CO CH2=CHCH2CH3 + O3  0.35 C2H5CHO + 0.63 H2CO + 0.41OH Rate = -(kOH[OH] + kNO3[NO3] + kO3[O3]) [1-butene] Rate = -keff [1-butene] VOC’s ZA = f(Lat, Lon, DOY, Time of day) CO O3 Location (lat, lon) Example Results CWA: Atmospheric Reactions of Sarin (GB) kOH kNO3 Concept T&D Only vs T&D + Chemistry CH3-P(=O)(-F)(-CH(CH3)2) + OH Degradation Product (Sarin) CH3-P(=O)(-F)(-CH(CH3)2) + NO3  Degradation Product Rate = -(kOH[OH] + kNO3[NO3]) [Sarin] Rate = -keff [Sarin] Pollutant + OH, NO3, O3, etc. CWAs kOH, kNO3, kO3, etc. Degradation products Transport, diffusion, and chemical reactivity • Strategy • Implement Algorithm into SCIPUFF / HPAC • Develop a chemistry module (currently called degrade.dll) that interfaces with the dispersion algorithms in SCIPUFF. • Develop data for algorithm for the atmospheric degradation of TICs / CWAs • Requirements specified for development of the chemistry algorithm: • The algorithm must run rapidly and not impact model wall clock run-time • The algorithm must account for all modeling scenarios encompassing a wide range of meteorological conditions (i.e., changes in cloud cover, temperature, ambient conditions, etc.). • The algorithm must be robust enough to account for diurnal changes to the degradation rates of TICs and CWAs. • The algorithm should account for the potential generation of intermediate toxic compounds. In some cases it may be possible for the degradation products to be more toxic than the pollutant that was released. • Data Development • Translate C(t) data to keff using the following: • Fit keff data to a series of polynomials and determine the best polynomial function. • The polynomial algorithms are a function of meteorological parameters (i.e., T, SE, CC, time of day, [H2O], etc., and ambient concentrations of indigenous atmospheric species (OH, O3, VOCs, NO3). Ambient concentrations are associated with five super classes of Land Use (Urban, Grassland, Forest, Desert, and Water) Generate c(t) data Calculated Plume is TIC Dependent Mechanism ID Rxn’s, EA, k(T) (w/ OH, NO3, H2O, O3, etc.) Implement TIC / CWA Data in Detailed Model such as the CBM Decomposition of Butene as f(Latitude) Run Photochemical Box Model (PBM) as a f(met parm’s) [Butene] as f(time of day) T = 290 K Land use = Urban Latitude = 25 – 50° N [Butene] [ppm] 50° Obtain cTIC(t) as f(met parm’s) Populate SCIPUFF w/ keff data Derive Empirical keff (met parm’s) 25° Time of day [hrs from midnight] Implementation of Algorithm in SCIPUFF Tracking of Reactant and Product(s) Translate to keff Plume contours of 1-butene and propanal (product) at 4 and 8 hrs after release (Urban scenario for 2 hour continuous release of 1-butene) 1-butene propanal • Summary • An atmospheric chemistry capability that does not impact model run time was incorporated into SCIPUFF. • Algorithms were developed for the atmospheric degradation of nine alkenes, H2S, and Sarin. • The effective degradation rates (keff) for TICs and CWAs are describe by a series of developed polynomial functions that are a function of important meteorological parameters • Temperature, solar elevation, cloud cover, time of day, moisture level, latitude, ambient conditions (Land use is used as a surrogate for air quality) • The algorithm can account for the formation of degradation products (e.g., propanal from 1-butene) • Future plans are to increase the data base to include other TICs and CWAs.