United States
Environmental Protection
Agency
Atmospheric Research and Exposure
Assessment Laboratory
Research Triangle Park NC 27711
Research and Development
EPA/600/S3-90/017 June 1990
Project Summary
Urban Aerosol Transformation
and Transport Modeling
Y.Seoand J. R. Brock
This project has been concerned
with development of an urban aerosol
model which includes the dynamical
processes shaping the aerosol size
and composition distributions. A K-
theory model, termed AROSOL, for
the super- and sub-micrometer aer-
osol mass concentration has been
developed and tested with urban air
pollution data. This report deals with
the development and inclusion of
computer modules for description of
the dynamics of single component
and binary aerosols. Current work
has proceeded along several lines.
The data bases from the EPA Phil-
adelphia Aerosol Field Study (PAFS)
have been examined and corrected
for evaluation of AROSOL for sulfate
aerosol modeling. Modules have
been included in AROSOL which can
account for chemical conversion, nu-
cleation, condensation, evaporation,
and coagulation as a step in the ex-
tension of AROSOL to multicompo-
nent aerosols. Finally, work has been
done on coupling the nucleation and
condensation/evaporation processes
to a suitable oxidant mechanism for
sulfate and nitrate formation. Be-
cause the PAFS data base and other
similar data bases are not sufficiently
complete, it has not been possible to
thoroughly evaluate the accuracy of
the computer modules.
This Project Summary was
developed by EPA's Atmospheric
Research and Exposure Assessment
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 adverse effects of air pollution
are well known: increased incidence of
respiratory diseases, reduced visibility,
economic loss, inadvertent weather
modification, and acid precipitation, to
name a few. The urban aerosol plays an
important role in these adverse effects
An understanding of this role requires,
among other factors, knowledge of the
aerosol dynamical processes shaping the
aerosol size and composition distribu-
tions. These dynamical processes in-
clude advection, dispersion, deposition,
primary and secondary source input,
nucleation, condensation/evaporation, and
coagulation. Models for the atmospheric
evolution of particle size and composition
distributions reflecting these dynamic
processes will ultimately be necessary
for development of realistic aerosol air
quality regulations and control strategies.
This project has been concerned
with development of urban aerosol
models which include the dynamical
processes shaping the aerosol size and
composition distributions. The first part of
this work has involved evaluation of data
bases and a K-theory model, termed
AROSOL, for the super- and sub-
micrometer aerosol mass concentration.
Recent and some current work has been
devoted to inclusion and development of
computer modules for description of the
coagulation and condensation evapora-
tion processes for single and multicom-
ponent aerosols. The major part of
current work has proceeded along
several lines. The data bases from the
EPA Philadelphia Aerosol Field Study
(PAFS) have been consolidated and
corrected for evaluation of AROSOL for
sulfate aerosol modeling. Modules have
been included in AROSOL which can
account for chemical conversion, nuclea-
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and aerosol modules'?hatOf the cnernica'
The modules for seconrS available.
nitrate formation havPh^ Sulfate ancl
*'th data from th- 7no" de.monstrated
surement data hese '.fTI? and
analysis optfons 'of mnH° Ude sta«s"cal
recommended by EP! eVa'Uati°n as
spectral analysis. wel1 as
9rid Consists
""cknes
rr 7
very large and a thf
relative "humTdity ,'
conditions are not
' ii LI ait/
MARS can also oe used tn *
•mately aqueous phase ox d approx-
ozone and Mn LnV Pnydr°9en peroxide,
MARS provides a rnn CatlOn Cata'ysts.
estimate of nart^n en'ent and rap.d
species between aeroT? °f the Stated
However, it must be n rian 93S pnase.
does not address nn*??.! tne model
this partitioninVby SSer -- a'terati°n Of
constituents, and ft - •
LSODE
known
na onen .- p^
for this approach hJfh6 fation-
explicitly. The cnnwh , een shown
Processes for mese S'°"S to the
indicated schemafca^y 6
°f
conditions
of data
and stability
*"
ran9e
CBM IV tht isrCUeS (he versi°" of
-
<3) (rate of chane due to
tion) to
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Advection Dispersion Dry Deposition Chemistry Aerosol Dynamics
Figure 1. Schematic diagram of structure of urban aerosol model AROSOL
Empirical Model
Meagher (EMM)
CB - IV
Atkinson-
Uoyd
Figure 2. Options in AROSOL for
calculation of homogeneous
gas phase reactions.
AROSOL Dynamics
Lumped
Aerosol
Model
(LAM)
Aerosol
Dynamics
Model
(ADM)
Model for an
Aerosol
Reacting
System
(MARS)
Figure 3. Schematic diagram of aerosol
dynamics options available in
AROSOL.
It may be noted that the coagulation
process does not enter since the total
mass concentration is conserved by
coagulation; coagulation does not alter
the mass concentrations but does change
the composition distribution. The limit-
ation of LAM appears in the aerosol rate
processes, (3), (4), (5), and (6) which all
require knowledge of the particle size
distribution. Current practice is to treat
such rate processes in an empirical or
semi-empincal manner whose general
validity is unknown. If heterogeneous
conversion processes are negligible, the
rate of formation of a species' particulate
mass concentration is assumed to be
equal to the rate of production of vapor
phase mass concentration by chemical
reaction. For those species depositing
entirely in the aerosol phase, this
assumption appears to be acceptable. Of
course, for a species such as nitrate, the
LAM must be supplemented with an
equilibrium model such as MARS.
For the atmospheric aerosol, the
aerosol dynamics model (ADM) is formu-
lated in its most general form in terms of
the distribution function for a multi-
component aerosol. As yet, such a
general formulation cannot be validated
owing to lack of field data. A module is
included in AROSOL under ADM for
binary homogeneous nucleation, con-
densation/evaporation and coagulation.
This module is termed the binary aerosol
dynamics model (BADM) and is intended
for simulation of new particle formation
by binary homogeneous nucleation which
may occur, for example, during oxidation
of S02 in urban plumes. BADM uses a
moment method for computational effic-
iency, although very accurate modules
have also been developed for com-
parative purposes. As this module was
developed only recently as part of this
work, it will be outlined here.
A binary aerosol is described by its
distribution, n(m1,m2,x,y,z,t), where
ndm1dm2 is the number of particles
having masses of species 1 and 2 in the
ranges pr^dm, and m2dm2 at spatial
point x,y,z at time t. The evolution of n is
followed through several of its moments,
Mij:
My =//m1lm2J n(m1,m2) dm1dm2 (1)
where the integration is over all masses
m-| and m2. The moments necessary for
homogeneous nucleation and particle
growth are M00 (the total particle number
concentration), M10, M0i , M20, and M02.
For simplicity, the coagulation term
will be omitted in this description; it is,
however, included in the general moment
formulation. When particle growth occurs
by binary nucleation and condensation/
evaporation processes, the evolution
equation for n has the form
an/at
= (a/am1)(G1n) - (a/dm2)(G2n) + R12 (2)
where G-), G2 are the particle growth
rates for 1 and 2 and R12 is the binary
nucleation rate. From equations (1) and
(2) rate equations for the moments M10
M0t M20, and M02 are easily derived.
G! and G2 are the noncontinuuum
growth rates and include the Kelvin effect
and activity coefficients for the mixture.
The expression for R12 may be taken
from the classical theory of binary
homogeneous nucleation with its modif-
ications. These modifications include
nucleation in the presence of existing
particles.
The moment equations are not
closed; closure is in general not possible.
Closure is achieved here by using a
parameterized form for the distribution n.
It is assumed that in the atmosphere, the
mixture of secondary and primary par-
ticles is an intrinsic mixture in that all
particles will contain both species 1 and
2. For this case, closure is obtained with
the model:
n(m1,m2)M00f1(m1)f2(m2) (3)
where the fj are lognormal frequencies:
fi =(2iO - 1/2(1/1*1^^)
exp(- In2(m/mavj)/2ln2nj)
and mavi and m. are respectively the
mean mass and geometric standard
deviation for species i. These parameters
are easily expressed in terms of the
moments defined above.
The validity of this moment method
has been studied in two ways. First, \r
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f/)e absenr
*r°«th $*
con V accoun,;/, f^se rZ /Or f/1e
- QOO/ u 't'lriiQatJn^ _uus r(=lri —
^^/ss/nr,^ . ^fe cnn»^.-_ rria'n/'no rea
r-» - ^
9'ven hi/ c.of su/ffl^ n/i 'nc/ur/o. °'
— ^er So are; (7) .a model
rer
no n °rd
prec'P
l
Hit
mese fw0
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models. The interpretation of these
various differences is not possible owing
to the lack of detailed information for the
NMOC in the PAFS data base. Also, the
hydrocarbon data available in PAFS are
known to be inaccurate. For this same
same study period, MARS was used to
demonstrate secondary sulfate speciation
from the conversions given by CBM; as
would be expected, the gas sulfate is
very small and virtually all the sulfate
resides in the aqueous aerosol. Also from
the CBM calculations, nitrate speciation
calculated by MARS was also obtained.
Based on the assumed background
ammonia levels, MARS predicts that all
the nitrate resides in the gas phase with
no aqueous or particulate nitrate; the
relative humidity during this period was
approximately 50%, a value too small to
shift the equilibrium toward aqueous
phase ammonium nitrate. It is possible
that these findings would need to be
modified if contributions of nitrate and
sulfate from background and fumigation
had been considered.
In all the simulations with CBM for
sulfate, low sulfate formation in the
modeling domain was found. There are a
number of possible reasons for this. First,
as noted above, the hydrocarbon data
from PAFS are known to be inaccurate;
water interferences are now known to
have been present in the analyzers; this
results in hydrocarbon values that are too
low. Therefore, the resultant sulfate
conversion/deposition rates are too small.
Also, with limited data on hydrocarbon
speciation available, assumptions accord-
ing to the EKMA procedure were
necessary; these assumptions may not
have been valid for the modeling domain.
Finally, the large differences in sulfate
conversion given by the CBM and ERT
ALM models indicate difficulties in
applying current kinetic models.
Urban scale aerosol models of the
future most likely will need to deal more
effectively with some essential problems
characteristic of the urban scale. Two of
these are: (1) Data bases resolved with
small time and length scales; (2)
Reaction and turbulent mixing at small
time and length scales. The first of these
will probably require advances in low cost
field measurement technology. The
second problem, in the context of
Eulerian models, must involve develop-
ment of subgrid scale models which
account for the fact that in many urban
areas pollutant transport and transforma-
tion involve reaction, mixing, and
entrainment by plumes over relatively
small time and length scales.
Further research should be designed
to lead to valid models for urban scale
photochemical reactions and for aerosol
formation applied in simulation of reaction
in atmospheric turbulence. The current
lumped parameter (semiempirical) mod-
els in use, such as CBM and ALM, have
apparently not been tested for
concentration fluctuations with frequen-
cies characteristic of the urban scale. In
anticipation of the need, it is suggested
that it would be useful to begin to direct
some smog chamber and field studies
toward obtaining the necessary infor-
mation for semiempirical models suitable
for reactive plume modeling.
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Y. Seo and J.R.Brock are with the University of Texas, Austin, TX 78712.
H.M. Barnes is the EPA Project Officer (see below).
The complete report, entitled "Urban Aerosol Transformation and Transport
Modeling," (Order No. PB-90 187 1701 AS; Cost: $17.00, subject to change)
will be available only from:
National Technical Information Service
5285 Port Royal Road
Springfield, VA22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted at:
Atmospheric Research and Exposure Assessment 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/S3-90/017
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