8A.6   AIR QUALITY MODELING OF PM AND AIR TOXICS AT NEIGHBORHOOD SCALES

                                         Jason Ching*
                             Atmospheric Sciences Modeling Division
                                    Air Resources Laboratory
                         National Oceanic and Atmospheric Administration
                                Research Triangle Park, NC 27711
 1  INTRODUCTION
    The current interest in fine particles and toxics
 pollutants provide an  impetus  for extending  air
 quality  modeling  capability  towards improving
 exposure modeling  and  assessments.  Human
 exposure   models   require   information   on
 concentration  derived  from  interpolation  of
 observations taken  from  monitoring networks.
 Causal mechanisms  for adverse  health  from
 particuiate matter and other  air pollutants are
 numerous, but not well understood; however they
provide much of the  rationale for the  nation's PM
 research portfolio (NRC 98, 99). The NRG listed 10
 causal hypotheses, each relating to some physical
 aspect or speciation  of PM, and/or toxic pollutant
 species. The distribution of concentration fields for
 different PM causal pollutants will be highly complex
 at neighborhood scales.  However, the number of
 locations of samplers of typical networks in urban
 areas is generally sparse; also, due to the sheer
 myriad  of PM  and  toxic substances,  temporal
 sampling of physical  parameters of PM, speciated
 PM and toxic pollutants  are  limited and varied
 varying from sub-hourly to daily or weekly samples,
 and/or are surmised as surrogates of the available
 measurements.    Thus,  clearly,  the  observed
 temporal and spatial concentration fields are poorly,
 or  inadequately  resolved  for  driving  exposure
 models and conducting health risk assessments.
 Currently  the EPA  emissions based  modeling
 systems,   ModeIs-3 Community  Multiscale   Air
 Quality Modeling System (CMAQ) (Byun and Ching,
 1999) is capable of modeling PM 2.5 and PM-10 at
 horizontal resolutions of ~36km for regional to 4 km
 for urban  scale  predictions.  Urban areas are
 sources  of  large amounts  of  pollutants that
 contribute  to significant and  inherently  subgrid
 spatial variability of the concentration fields and to
 subsequent exposures. Stationary monitors will be

 *On assignment to the National Exposure Research
 Laboratory, U.S. Environmental Protection Agency
 Corresponding  Address: Atmospheric  Modeling
 Division, NERL, USEPA (MD-80), RTP, NC 27711
 email address: ching.jason@epa.gov
unable to characterize this variability.   Current
Eulerian-based air quality models' spatial resolution
is coarse and cannot resolve the fine scale details.
The modeling of dispersion of local sources ignores
the regional background. Modeling methodologies
and parameterization techniques for the transport
and dispersion of these local sources in complex
urban canyons are limited.  Methods to serve as a
bridge between these modeling and monitoring
approaches to determine concentration variation
arising from the juxtaposition of concentration from
the regional and urban sources are needed.
   In this presentation, a framework for extending
the Models-3/CMAQ to be operable at a full range
of scales from regional to the neighborhood  scale
for use in exposure modeling is described. As part
of this  study,  methodologies  and  approaches
envisioned  to  develop  rational linkages   with
ambient  and  exposure   monitors  to  provide
concentration fields as critical inputs to models of
human exposure (and epidemiologicai studies) are
discussed.  This initial study includes refining the
model scales to grid sizes of order 1 km, to develop
the  sub-grid   scale  parameterizations   and
subsequently,  to  deriving functional  linkages
between the modeling and  the ambient fixed site
and  personal  exposure  monitoring  data,  and
incorporates in the  implementation,  physical flow
modeling and  visualization, computational  fluid
dynamics  modeling and  statistical  techniques.
Specific  aspects  under   study   include  the
development  of   functional  relationships  that
provides a mapping across space and time between
the modeled and monitored fields, considerations of
sensitivities  to  model grid resolution, and for
different emissions scenarios, for different and full
ranges of averaging time periods from hourly  to
annual fields. The effort will include methods for
modeling exposures for a variety of human activity
patterns.

2. PROBLEM DEFINITION
   The following discussion provides a conceptual
framework and thus the basis of the requirements

-------
for the study. Given:

Exposure =    SUM [Joint (Activity (x,y,P(t)) X
               Concentration (x, y, t))] Time
where
Activity
    Actual  and/or  patterns of human  activity
    including the actual time, t, the time period (P(t))
    spent outdoors,  the  time  and  pattern  of
    commuting to and from micro  environments,
    and the time spent indoors  in  the  various
    micro environments. Information needs include
    the locations (x, y) where activity occurs.
Concentration:
    Ambient spatial (x, y) distribution and temporal
    variations (t) of each and all transported primary
    and secondary  pollutants,  and those freshly
    dispersed pollutant sources in the urban areas
    and in different micro  environments. These
    fields are influenced by the  exchange between
    the micro environments and the ambient air.
Time:
    Temporal interval  for acute (days to months)
    and for chronic (months to years) responses for
    time intervals, P, for which significant exposure
    in given activity takes place (minutes to hours).

    Current  approaches for  modeling ambient
concentration  fields  at urban to  neighborhood
scales for PM and toxics do not yet exist or are
overly simplistic.  Urban  scale grid  models  are
unable to depict spatial variation from sources at
subgrid scales.  Dispersion models developed to
handle local scale sources do not handle secondary
pollutants.    Representation  of transport  and
dispersion for use  in urban air quality models,
especially for  PM  and  Toxics  pollutants  is a
problem. The modeling of the spatial and temporal
distribution of these trace pollutants  will  depend
highly on the representation of the transport field
affecting the dispersion of the sources.  The mere
introduction   of  parameterization  of  building
structures  in   urban   canopy  into   mesoscale
meteorological models, will increase the drag, and
turbulence causing enhanced horizontal dispersion.
However, the flow and dispersion  in street canyons
will in general differ significantly from grid resolved
wind  fields  for which  street  canyons are  but
roughness elements of an  urban canopy (Brown
and Williams, 1998, Brown et al, 1998).  They
demonstrate for subgrid features such as buildings
and street canyons that pollutant trapping occurred
in  street cavities  building  up  the  levels  of
concentrations, and some pollutants are transported
upwind of the buildings due to  recirculating flows;
additionally, the enhanced vertical dispersion due to
the presence of buildings caused pollutants to be
dispersed further downwind by faster moving winds.
    Additionally, the PM and toxic pollutants will
undergo  changes  in both  their  physical  and
chemical properties during transport and dispersion.
Many toxic pollutants are semivolatile at ambient
conditions and thus can either absorb and/or adsorb
onto  ambient  particles,  thus  adding additional
degrees of complication. Exacerbating the modeling
problem is the sheer numbers of toxic pollutants
that will be under consideration. Grouping of HAPS
compounds  by toxicity  classes,  by  degree of
reactivity, by volatility, and by the use of surrogates
are modeling approaches that may be used  for
initial implementation.
    Human exposure depends on time spent in
outdoor and in various micro environments. The
pollutant concentration in  micro environments such
as homes, schools, workplace,  vehicles, etc., will
depend on both the internal sources and as well as
exchanges between these micro environments and
the ambient air. Personal exposure  to  ambient
levels of such pollutants will depend not only on the
duration of time spent in each of the various micro
environments, but the time and location of activity,
because pollutant concentration is time and space
variant. The sum of the product  of activity  and
concentration is the cumulative exposure over some
time period, from relatively  short  term, acute to
longer term, chronic.

3. Study Approach
    The goal of developing  neighborhood scale
modeling capability to resolve concentration fields
at neighborhood scales  begins with a  systems
review, including identifying and reviewing the major
modeling components, followed by implementation
of optional approaches, demonstration and testing
phase, and methodologies for practical operations.
Figure 1  identifies several major components to be
investigated in  this study. These components are
discussed below:

3.1 Methodology for Handling Emissions Data:
    Local  sources  may  be  either, (a)  modeled
separately   using   local  dispersion   modeling
techniques to provide a basis for determining sub-
grid resolved concentration fields in urban canyons
for further use in exposure assessments or,  (b)
incorporated, somehow,  as inputs to gridded air
quality simulation models.  In the latter case, the
development and testing of  methodology(s)  for
preparing gridded emission from the sub-grid scale
sources is reviewed.

-------
     Tools     Data
   Concentration Fields
  High Resolution         Activity
                        Exposure
                        Timescale
    Detailed Database
    —-Emissions
    —-Meteorology
      •Building data
        (Monitoring \
         Network /
        (Computational \
           Fluid      /
          Dynamics  /

            1
            Extend
       Mode!s-3/CMAQ
       to Neighborhood
            Scales
Exchanges
Ambient-
Micro-Environments
                                                      Human
                                                      Activity
          Physical
          Modeling
  VFlow
'isualtzation
Figure 1.  Design components of Neighborhood scale airquality simulation mode! of PM and Toxic pollutants
3,2 CFD (Computational Fluid Dynamics Model):
    Numerical experiments conducted to examine
the  dispersion  and  the  concentration  fields
associated with emissions in conceptualized street
canyons with varying degrees of complexities and
configurations will  provide bases for subsequent
investigations and development  of  parametric
methodologies fordetaited treatments of the subgrid
variability  in  gridded air quality models.   The
experiments  will  incorporate  increasingly  more
complex descriptions of dispersion, chemistry and
deposition.    Guidance   for  more operational
techniques will be an objective.

3.3 Physical Modeling and Flow Visualization:
    Physical   modeling   and  flow  visualization
experiments will be conducted to provide a basis
for the testing of  CFD modeling results,  and to
develop and  test methodologies for gridding sub-
grid scale emissions and for examining details of
the sub-grid scale  transport and dispersion. Early
                    results of flows over scaled series of 2-D array of
                    buildings in the USEPA Fluid Modeling  Facility's
                    wind tunnel show changes in the degree of flow
                    perturbations downwind from the leading edge of a
                    series of 2-D array of modeled buildings. Such flow
                    complexities  provide  a  challenging  basis  for
                    evaluating  CFD   models.  Carefully  designed
                    experiments will help guide the development of the
                    parameterizations of dispersion and transport in the
                    air quality models.

                    3.4 Modeling and Processes Research:
                        The Models-3/CMAQ will  be set up to operate
                    with additional nesting at finer grid resolutions  to
                    the current 36, 12 and 4 km set.  To achieve this,
                    this study will involve tasks to prepare emission and
                    meteorology modeling,  input data  and science
                    algorithms  at  commensurate   grid  resolution.
                    Sensitivity and process analyses will be conducted
                    to investigate and to understand the response and
                    contribution of different science process modules

-------
and other necessary parameterizations to modeling
at grid resolutions of order 1 km or less.

3.5 Links with monitoring data:
    This project will explore and develop practical
methodology that will relate both fixed site and
personal monitoring data to model outputs at four
(and 1,3) km. Numerical and physical modeling will
provide an opportunity to capture the concentration
fields with  high  temporal and  very fine  spatial
resolution.  Monitoring data provide ground truth
information  to  check  and  to  evaluate  model
predictions, and  is typically the basis for driving
exposure models. Candidate approaches such as
Neural Networking and/orothergeospatial-temporal
mapping  will  be  investigated.   The  resulting
functional fields will greatly enhance the running of
exposure models. An additional spinoff from this
study will be to improve the siting strategy  for
deploying monitors.

3.6 Links with Exposure Models:
    Develop   and   subsequently  demonstrate
methodology for computing exposures for different
emissions scenarios, including  traffic,  point/area
sources for different integration time periods from
one  hour to  annual and  for  different  human
exposure ^situations such as in traffic, outdoor and
indoor exposures, and  for different  susceptible
populations.  The concentration  information  will
include speciation of PM-2.5 to address health
impact hypotheses such as by  total  mass, size
distribution, numberdensity (especially for the ultra-
fine particles), and by speciation including  unique
properties such as acidity, oxidizing capacity, trace
metals, and toxicity.

4. DISCUSSION  AND SUMMARY
     This project is expected to develop Eulerian
based air quality modeling  methodology(s) and
capability(s) to support human exposure modeling
and  investigations  testing  the various  health
hypotheses  concerning adverse health effects by
various pollutants (NRC98.99).  It has a follow-on
benefit to addressing urban toxics exposure issues.
The  project  is currently  being implemented by a
team of   NOAA and  EPA scientists and their
collaborators to develop and study methods  for
integrating Eulerian models for urban  scales with
local scale models (using a combination of CFD and
physical modeling which account for urban canopy
and local emissions sources including traffic as well
as point/area sources of pollutants). The project will
include  but  not be  limited  to  deriving  various
functional linkages between the Models-3/CMAQ
emissions based modeling system concentration
fields of key particulate matter parameters with
ambient  fixed   site  and   personal  exposure
monitoring  data, and to incorporating into  the
methodologies,  flow visualization, computational
fluid dynamics modeling and statistical techniques.
The project  will  further  develop  and  derive
functional relationships that  provide a mapping
across space and time between the modeled and
monitored fields. The investigation will include a
variety of studies including sensitivities to model
grid resolution, examination of a variety of different
emissions scenarios, and identifying and  testing
methods for handling the full range of averaging
time periods from hourly to annual fields. The effort
will include developing methods  for  modeling
exposures for a variety of human activity patterns.
In this demonstration project, one or more candidate
urban  areas   will  be  selected  for detailed
investigations. Criteria for  selection include  the
existence of PM sampling databases and detailed
emissions inventories

Disclaimer: This paper has been  reviewed in
accordance with the U.S. Environmental Protection
Agency's peer and administrative review policies
and approved for  presentation and publication.
Mention of trade names or commercial products
does   not  constitute    endorsement   or
recommendation for use.

References:
Brown, Michael, Cathrin Muller, 1997: The effect of
    micro scale urban canyon flow on mesoscale
    puff dispersion. 12th Symposium on Boundary
    Layers  and   Turbulence.  Vancouver  BC,
    American Meteorological Society, 463-464.

Brown, Michael J., and Michael D. Williams, 1998:
    An   urban   canopy   parameterization  for
    mesoscale  meteorological models. Second
    Urban   Environment   Symposium.,  13th
    Conference   on   Biometeorology  and
    Aerobiology, Albuquerque,  NM.,  American
    Meteorological Society,144-147.

Byun,  D.W. and  Ching,  J.K.S.,  1999, Editors:
    Science Algorithms of  the  EPA  Models-3
    Community  Multiscale Air  Quality (CMAQ)
    Modeling System. EPA- 600/R-99/030, ORD,
    U.S. Environmental Protection Agency

NRG (National Research Council) 1998: Research
    Priorities  for Airborne  Particulate  Matter. I.
    Immediate  Priorities  and  a  Long-  Range

-------
    Research Portfolio., Washington DC., National
    Academy Press.

NRC (National Research Council) 1999: Research
    Priorities  for Airborne Particulate  Matter.  II.
    Evaluating Research Progress and Updating
    the  Portfolio.,  Washington  DC,,  National
    Academy Press.

-------
    NERL-RTP-00663
TECHNICAL  REPORT  DATA
1. REPORT NO,

   1PA/600/A-00/018
  . TITLE AND  SUBTITLE
Air Quality Modeling of  PM  and  Air  Toxics  at
Neighborhood  Scales
                                                                      8.PERFORMING ORGANIZATION REPORT NO.
Jason  China
9. PERFORMING ORGANIZATION NAME'AND ADDRESS

Same  as Block 12
U.S.  Environmental  Protection Agency
Office of  Research  and Development
National Exposure Research  Laboratory
Research Triangle Park,  NC  27711
                                13.TYPE OF REPORT AND PERIOD  COVERED

                                Extended Abstract,  FY-00
                                14..SPONSORING AGENCY CODE

                                EPA/600/9
16. ABSTRACT

INTRODUCTION The current interest in fine particles and toxics pollutants provide an impetus for extending air quality modeling
capability towards improving exposure modeling and assessments. Human exposure models require information on concentration
derived from interpolation of observations taken from monitoring networks. Causal mechanisms for adverse health from particulate
matter and other air pollutants are numerous, but not well understood; however it provides much of the rationale for the nation's
PMresearch portfolio (NRC 98, 99). The NRC listed  10 causal hypotheses, each relating to  some physical aspect or speciation
of PM, and/or toxic  pollutant species. The distribution of concentration fields for different PM causal pollutants will be highly
complex at neighborhood scales. However, the number of locations of samplers of typical networks in urban areas is generally
sparse; also, due to the sheer myriad of PM and toxic substances, temporal sampling of physical parameters of PM, speciated
PM and toxic pollutants  are limited and varied varying  from sub-hourly to daily  or weekly samples, and/or are surmised as
surrogates of the available measurements.  Thus, clearly, the observed temporal and spatial concentration fields are poorly, or
inadequately resolved for driving exposure models and conducting health risk assessments.  Currently the EPA emissions based
modeling systems,  Models-3 Community Multiscale  Air Quality Modeling System  (CMAQ) (Byun and Ching, 1999) is capable
of modeling PM 2.5  and PM-10 at horizontal resolutions of ~36km for regional to 4 km for urban scale predictions. Urban areas
are sources of large amounts of  pollutants  that contribute  to significant and  inherently subgrid spatial variability of the
concentration fields and  to subsequent exposures.   Stationary monitors will be unable  to characterize this variability.  Current
Eulerlan-based air quality models' spatial resolution is  coarse and cannot resolve the fine scale details. The modeling of dispersion
of local sources ignores the regional background. Modeling methodologies and parameterization techniques for the transport
and dispersion of these local sources in complex urban canyons  are limited.	
17.
                                       KEY WORDS AND DOCUMENT ANALYSIS
                     DESCRIPTORS
                                                        ^IDENTIFIERS/ OPEN ENDED TERMS
                                                                                         o.COSATI
18. DISTRIBUTION STATEMENT

RELEASE TO PUBLIC
                  19, SECURITY CLASS (This Report)

                  UNCLASSIFIED
                                                                                         21 .NO. OF PAGES
                                                        20. SECURITY CLASS (This Page)

                                                        UNCLASSIFIED
                                                                                         22. PRICE

-------