Health Physics

at the two successive particle positions, mtegratmg over

the duration of the time-step, and then adding the
displacement to the imtial position of the particle The
imtegration time-step can vary from | to 60 min but 1s
bound by a user-specified advection distance per trmestep to limit the advectionto less than one grid pomt per


Dispersion 1s computedafter the advection compu-

tation, however, 1t 18 necessary for the model to first

compute stability and mixing coefficients Stabihty and
mixing are estrmated from the meteorological input data
Heat and momentum fluxes, 1f they are present m the
meteorological data, are used to compute the stability,
otherwise temperature and wind data at each grid pomt
are used to estimate it Vertical mixmg withm the
boundary layer 1s computed as an average at each
horizontal grid pomt based upon flux data Above the
boundary layer, vertical mixmg 1s estimated from the
wind and temperature profiles Horizontal mixmg 1s
computed usmg the deformations m the wid field and 1s
adjusted based on the size of the meteorological grid
Toreahstically simulate the dispersive nature of the
atmosphere, a random turbulent component 1s mcorporated mto the dispersion calculation by adding the turbulent component to the mean velocity obtamed from the
meteorological mput data at each trme-step This turbulent component 1s a Gaussian based pseudo-randomly
generated number resultmg from the product of the
Gaussian random number and the standard deviation of
the computed turbulent velocity of the velocity vector
(Draxler and Hess 1997) The Gaussian random number

is generated usmg a variation of the lmear congruential

method, X,,, = (aX, + c) mod m, where the element 1

indicates the position of the random number withm the
sequence When the parameters a, c, and m are chosen

correctly, generatorsofthis class can ensure a nonrepeating sequence on thescale of 10° It should be noted that
though the HYSPLIT model mcorporates a random

turbulence element, the model 1s not stochastic because

the same random sequence1s generated with each mvo-

cation of the model, meanmg that the model results for

any single simulation will always be the same assuming
the simulation parameters are not changed This can be
altered by simply modifymg the model’s random number
algorithm to apply a different seed value with each


Several dry deposition options are available to the
model user In our case, dry deposition was simulated
under the assumption that the deposition velocity for all
particles was equivalent to the gravitanonal setthng
velocity For local fallout from weaponstests, this 1s a
reasonable approximation smce most ofthe radioactivity
is found on particles of diameter greater than 5 yam

August 2010, Volume 99, Number 2
(Heidt et al

1953, Crocker et al

1965, Ibrahim et al

2010) Other HYSPLIT options mclude implicitly specifymg a dry deposition velocity or usmg the resistance
method (Draxler and Hess 1997)

In our simulations,

gravitational setthng was computed by the model based
on particle diameter, a fixed particle density of 25 g
em”, anda fixed spherical particle shape The computed
setthng velocity 1s applied to the vertical position of the
particle at each time-step Particles are subject to dry
deposition removal processes upon entering the model’s
surface layer The model computes dry deposition using
one of two options either removing a fraction of the
particle’s mass over successive time-steps unti] the mass
becomes zero, or computing the probability that a partcle will deposit all of 1ts mass during a single time-step
(Draxler and Hess 1997) In our simulations the depost-

tion probability option was used
Wet deposition processes impose difficulties m
meteorological computer models The difficulty stems
from the simplified assumptions incorporated ito wet
deposition models coupled with a general Jack of rehable
precipitation observations m the meteorological mput
data (Draxler and Hess 1997) Both m-cloud (ramout)
and below-cloud (washout) wet deposition are estimated

im the HYSPLIT model by defming thefraction of total
pollutant mass within and below the cloud layer and
applymg an estimated deposition rate The extent of the
cloud layer 1s defmed usmg relative humidity (RH) in
the meteorological profile at each horizontal grid point
The cloud top and bottom are, by default, defined at 60%
and 80% RH, respectively In the case of ramout, a wet

deposition velocity 1s calculated as the product of the
precipitation rate at the grid pomt anda pollutant-specific
scavenging ratio The scavenging ratio 1s based on the
amount ofpollutant (g L~') im the arr within the cloud to
that m the ram (g L~') measured on the ground atthe grid
pomt (Draxler 1999) The wet deposition velocity is then
apphedto the fraction of pollutant mass within the cloud
layer Below-cloud removal1s defined usmg only rate
constant (s~') and 1s mdependent of precrpitation rate
(Draxler and Hess 1997) The rate constant 1s applied to
the fraction ofpollutant that 1s below the cloud bottom
In our simulations, the model’s default values for the

tn-cloud scavengmg ratio (32 X 10° L per L) and the
below-cloud rate constant (50 X 107° s7') for wet

deposition processes were used
The total deposition over a time-step 1s the sum of
the removal amounts resutmg from each process The
total pollutant mass 1s then reduced by the computed

removal fraction (Draxler and Hess 1997)

Several verification examples demonstrating the
apphcability and accuracy of HY SPLIT computations in
the areas of particle advection, dispersion, and deposition

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