Models3 Community Multiscale Air Quality CMAQ Modeling System: OneAtmosphere Modeling

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Models-3 Community Multi-scale Air Quality
(CMAQ) Modeling System One-Atmosphere Modeling

• Daewon Byun
• University of Houston

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One-Atmosphere Concept

• First principles description of atmospheric
  system
• Handles interactions at different dynamic scales
  and among multi-pollutants with one modeling
  system

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One Atmosphere Concept

• Multiple scale atmospheric dynamics
• Meso-gamma, urban, regional, global scales
• Daily, episodic, seasonal, annual time scales
• Multiple atmospheric pollutants
• Ozone, acid deposition, eutrophication
• Fine particles, visibility
• Tracer transport
• Toxics

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Models-3 CMAQ Goals

• To evaluate the impact of air quality management
  practices
• To better probe, understand and simulate chemical
  and physical interactions in the atmosphere
• To make comprehensive AQ modeling more available
  to government, industry, academia, and
  stakeholders

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Development of Models-3 CMAQ

• Second generation AQMs
• Are comprehensive but clunker
• Deal single pollutant problem at limited scales
• Have ad hoc integration of science processes
• Rapid changes in computer technology
• Continued improvements in science
• Scalable, modular, extensible system for
  multi-scale multi-pollutants needed

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Pedigree of Models-3 CMAQ 1
2nd Gen. Models
Impact on Models-3
CMAQ Implementation
Urban Airshed Model-IV
Framework Prototype UAM GUIDE - proof of
concept Emissions Processor (EMS-95)
Models-3 Emissions Processing Projection
System (MEPPS) ? SMOKE Tool SMOKE
Regional Oxidant Model (ROM)
Modeling System Management Components in
Emissions CBM-IV
Concept for I/O API Biogenic Emissions
(BEIS-2)?BEIS3 Generalized QSSA Solver
Regional Acid Deposition Model (RADM)
Science Base Meteorology RADM-2
mechanism Operator Splitting Transport, Cloud,
Aqu. Chem Nesting
MCIP ICON/BCON CMAQ
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Pedigree of Models-3 CMAQ 2
2nd Gen. Models
Impact on Models-3
CMAQ Implementation
RADM-Particulate Model
Aerosol
Aerosol Process Module Modal approach
SAQM
Non-hydrostatic MAQSIP (prototype)
Generalized Meteorology CMAQ
Acid Deposition Oxidant model
Dry Deposition Model Evaluation (with RADM)
CMAQ Dry Deposition Module
STEM-II
Sensitivity Analysis
Sensitivity Method Developments
... and many others
... in various ways
Generalized Coordinate, SMVGEAR Solver, MEBI,
etc ... and in many different forms
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One atmosphere chemistry

• Chemistry mechanism reader
• Generalized chemistry solver
• Gas-, aqueous-phase atmospheric chemistry
• Fine particle modeling PM2.5 PM10 secondary,
  primary, speciated conc (mass number)
  visibility
• Toxics modeling (mercury, atrazine, PAH, etc)

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One atmosphere dynamics

• Describe atmospheric dynamics with fully
  compressible governing set of equations
• Hydrostatic/non-hydrostatic atmosphere
• Utilize generalized coordinate system
• Dynamic consistency in met. CTM
• Mass consistent transport in CMAQ

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Horizontal Coordinates
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Height and Pressure Vertical Coordinates

• Height coordinate
• Suitable for representing surface and PBL
  parameterizations
• Time independent and intuitive
• Pressure Coordinate
• Suitable for describing weather
• Often used for hydrostatic atmosphere
• Time dependant

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Time Independent Terrain-Influenced Coord.

• Terrain-influenced Height coordinates

Accounts for topography Time independent and
intuitive Often used for non-hydrostatic
atmosphere

• Terrain-influenced Reference Pressure

Sigma-z with logarithmic transformation
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Hydrostatic Pressure (normalized)
Time-Dependent Terrain-Influenced Coordinates
Step-mountain Eta Coordinate
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Atmospheric Diffusion Equation

• (a), (b) horizontal and vertical advection
• (c),(d) horizontal and vertical diffusion
• (e), (f) chemical reactions and emissions
• (g), (h), (i) cloud, plume-in-grid, and aerosol

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Pedigree of Vertical Coordinates
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Data Dependency in CMAQ CTM
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• Multi-pollutant Capability

• Ozone, Acid/Nitrogen Deposition, Fine
  Particles/Visibility
• Generalized chemistry mechanism description
• Generic chemistry numerical solver
• Comprehensive chemistry Gas/Aqueous/Aerosol
  phases

• Modular Science Code Structure

• Integration with Models-3 Framework

Conclusion
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Summary of Models-3 CMAQ 1
Process
2001 Release
2002 Extension
Meteorology
MM5 hydrostatic/Nonhydrostatic with Enhanced
surface-PBL Kuo/Betts Miller/Kain-Fritsch Pleim-Xi
u version
Meteorology-Chemistry Interface Processor
Generalized MCIP ( MM5) RADM Dry
Deposition Models-3 Dry Deposition
MCIP2 (V2/V3) F90 Met. Models (RAMS, ETA, etc.)
Other Interface Processors
Photolysis rate Table Method Constant and
Dynamic BC ECIP with Plume Rise PDM
Photolysis Analysis 4-D Processor
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Summary of CMAQ 2
Process
2001 Release
2002 Extension
Emission
Models-3 Emissions Processing and Projection
System
Sparse-Matrix Operating Kernel for Emissions
(SMOKE) SMOKE Tool
CMAQ Chemistry-Transport Model
Generalized coordinate Advection PPM,
Botts Diffusion K-theory Chemistry RADM-2,
CB-IV Generlized solvers QSSA SMVGEAR Aq.
Chem and cloudmixing Aerosol Secondary/Primary Vi
sibility One-way nesting Plume-in-Grid
AdvectionYAM, and others (?) DiffusionACM Chemis
try SAPRC Fast chem. solver Nest
(Two-way/Multi-level) Improved Cloud/Aq.
Chem Aerosol3
Analysis Visualization
Process Analysis MB IIR PAVE/VIS-5D Point Flyer
Plume-in-Grid Visualization
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Operations of Models-3 CMAQ
Some useful information can be found in

• Models-3 CMAQ User Guide Ch. 2 Ch. 14
• Appendix
• CCTM SOP (Standard Operating Procedure)
• Scripts_watchouts

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Mobile processing
MODELS-3 FLOW CHART
Point Area Mobile Biogenics
Point proc. plumerise
SMOKE merge all
Area processing
smkinven
Biogenics processing
concentration
CCTM
ICON BCON JPROC
MM5 data
MCIP
landuse data
LEGEND Data files
Processors
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CCTM RUNS
MET EMISS
JTABLE36 BCON36_prof ICON36_237
CTM_CONC.uh36 in WK/cctm36/2000236
run.cctm36.pa.237
run.cctm36.pa.init
MET EMISS
CTM_CONC.uh36 in WK/cctm36/2000237
And so on
JTABLE12 BCON12_conc ICON12_prof
JTABLE12 BCON12_conc ICON12_237
CTM_CONC.uh12 in WK/cctm12/2000236
run.cctm12.pa.init
run.cctm12.pa.237
MET EMISS
MET EMISS
CTM_CONC.uh12 in WK/cctm12/2000237
And so on
JTABLE04 BCON04_conc ICON04_prof
JTABLE04 BCON04_conc ICON04_237
CTM_CONC.uh04 in WK/cctm04/2000236
run.cctm04.pa.init
run.cctm04.pa.237
MET EMISS
MET EMISS
CTM_CONC.uh04 in WK/cctm04/2000237
And so on
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14.2.2.2 ECIP ECIP is the processor that
generates an hourly three-dimensional emission
input file for the CCTM. ECIP incorporates
emissions from separate area-source and major
point-source files, created by MEPPS into one
output file. The key inputs for ECIP are the
area emissions file(s), the stack parameter and
emission files for the point sources, and a set
of meteorological data files generated by the
MCIP All major point sources are subject to
plume-rise and initial vertical dispersion
processes before being allocated to a particular
vertical model layer. If plume-in-grid (PinG) is
not applied in CCTM, the MEPSEs must be included
with the other major point sources in the ECIP
processing. The default configuration in the
current CCTM version uses the ping_noop module IF
the plume-in-grid (PinG) operation is used in
CCTM, the MEPSE emissions file must be omitted in
the ECIP processing by setting the MEPSE logical
flag in the run script to FALSE. The MEPSE
emissions file should be included as a separate
direct input file to CCTM. The maximum number of
total major point sources is limited to 10,000,
and there is currently a limit of 100 MEPSE
sources when applying the PDM and PinG.
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14.2.2.5 JPROC CMAQs JPROC processor predicts
photolysis rates for various altitudes,
latitudes, and zenith angles. JPROC requires
vertical ozone profiles, temperature profiles,
and a profile of the aerosol number density for
use in a radiative transfer algorithm to produce
the photolysis rates for CMAQ. Currently, the
radiative transfer algorithm assumes clear-sky
conditions (no clouds present), and the CCTM then
attenuates for cloudiness. (See the phot module
in Section 14.2.2.7.) JPROC computes a table of
photo-dissociation rate constants for the
photolytic, gas chemistry reactions. These rates
are interpolated in CCTM to the specified time
and location. For more details and an explanation
of this processor, see Section 2.3.5.
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14.2.2.6 PDM The PDM is a processor that
generates an input file needed to apply the PinG
module in a CCTM simulation. PDM uses the MEPSE
stack parameter file from OUTPRO, a processor in
MEPPS, and meteorological data files from MCIP to
produce a data file composed of plume
dimensions, plume positions, and related
parameters. The technical approaches used to
treat the plume dispersion and transport are
described in Section 2.2.6. If the PinG module
will not be exercised in the CCTM simulation, PDM
processing can be neglected. The default
configuration in the current CCTM is for PinG not
to operate (ping_noop), so PDM processing can be
omitted. If no MEPSE sources were generated
during MEPPS emissions processing, PDM and PinG
cannot be exercised. There is a maximum limit of
100 MEPSE sources in a PDM simulation.
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14.2.2.7 CCTM The CCTM processor is the main
processor for the CMAQ modeling system where
the chemistry, transport, and removal of
pollutants are simulated, and pollutant
properties are predicted. CCTM includes 15
different process classes, and a default module
has been predesignated for each of these classes
in the release version of Models-3. The CCTM
structure (and that of all the input processors)
is based on the concept of module classes that
relate primarily to the operator-splitting
paradigm from which CCTM is built and executed.
There is one class for each science process and
also for the CCTM driver and utility modules. In
building the executable, the user must select one
module from each class. Each module contains all
the code files that relate to a particular
science process. For example, the horizontal
advection class contains different modules based
on different solver schemes. One may select the
Botts scheme module or the default Piecewise
Parabolic Method module. In the future, various
classes will be populated with more modules as
they are created by the contributing community of
scientists.
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14.2.2.7 CCTM (Continued) Each module within a
class also has a class driver, which is the
top-level routine within the module. It is at the
top of the call chain for that module. This class
driver presents a fixed name and calling
interface to the driver class routine SCIPROC
that calls all the science process modules. In
addition to various choices between modules in
the physical process classes, you may select
a no-operation module for some of the classes.
The effect of such a choice results in bypassing
the physical process. It merely returns control
to the SCIPROC driver class subroutine. No-operati
on modules are useful for studying certain
effects or diagnosing problems.
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CCTM Classes and Their Default Module Classes
Default Module Cloud Dynamics and Aqueous
Chemistry cloud_radm The CMAQ cloud_radm module
simulates three types of clouds, including
sub-grid convective precipitating clouds,
sub-grid non-precipitating clouds, and
grid-resolved clouds. The cloud_radm module
vertically redistributes pollutants for the
subgrid clouds, calculates in-cloud and
precipitation scavenging, performs aqueous
chemistry, and writes wet deposition amounts
to an output file. Photolysis phot This module
reads the table of photolysis rates (j-values)
generated by the input processor JPROC. Phot then
interpolates these j-values to individual grid
cells (both vertically and horizontally) and to
specified times of the day. This module also
applies a correction to these values to account
for cloud cover. .
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CCTM Classes and Their Default Module Classes
Default Module Aerosols aero3 The aerosol
module introduces fine (PM2.5) and coarse
particulate matter into the CCTM. Both number and
species mass concentrations are predicted for
three size ranges, or modes, represented by log
normal distribution functions. Particles in the
PM2.5 range are represented by the Aitken and
accumulation modes. Coarse mode particles are
represented by a third mode. The sum of mass
concentrations in the Aitken and accumulation
modes represents PM2.5, the sum of all three
modes forms an estimate of PM10. Aerosol
Deposition Velocity aero_depv Unlike gases, the
deposition velocity for particles must be
calculated from the aerosol size distribution, as
well as meteorological and land-use information.
This module calculates the size distribution from
the mass and number concentration for each of the
three modes and calculates the dry deposition
velocity. .
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CCTM Classes and Their Default Module Classes
Default Module Gas Phase Chemistry Solver
qssa/smvgear/mebi (Hertel) Horizontal
Advection hppm The piecewise parabolic method
(PPM) is used as the default method for
horizontal advection. In the PPM, the subgrid
distribution is described by a parabola in each
grid interval. PPM is a monotonic and positive
definite scheme, which is very desirable for
photochemical modeling. Vertical Advection
vppm The vertical advection module solves for the
vertical advection with no mass-exchange
boundary conditions at the bottom and top of the
model. In the CCTM, the PPM algorithm with
steepening procedure is implemented because there
may be a strong vertical gradient in the
species concentrations.
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CCTM Classes and Their Default Module Classes
Default Module Horizontal Diffusion unif The
default module for horizontal diffusion in CCTM
is an explicit eddy diffusion algorithm. The
horizontal eddy diffusivity is assumed to be
uniform but dependent on the grid size of
the model. The diffusivity is larger for a higher
resolution run where numerical diffusion due to
the advection process is smaller. Vertical
Diffusion vdiff In the default CCTM, a local
mixing scheme, eddy diffusion, is implemented for
vertical diffusion. Eddy diffusivity is estimated
using the same PBL similarity-based algorithm as
in RADM. Mass Consistency Adjustments
denrate The Byun 1999 algorithm is used as the
default module for correcting mass
inconsistency during the three-dimensional
advection calculations. This technique ensures
conservation of the mixing ratio.
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CCTM Classes and Their Default Module Classes
Default Module Driver ctm The Driver class
contains modules that control the execution of
the CCTM. The main program calls the subroutines
that set up the general execution sequence and
the routine that calls all the science process
driver subroutines. Currently, there is only
one module in the driver class. Other modules
that may be added in the future include those
that control multiple nested executions. Init
init The Init class contains the module that
initializes the model run (i.e., gets initial
concentration data), does some checking for
correct input file domain parameters and data
existence over the run, and then opens the output
concentration file.
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CCTM Classes and Their Default Module Classes
Default Module Couple gencoor The Couple class
contains the module that is called to perform
couple and decouple operations that affect the
concentration field array modified by each
science process. Coupling essentially changes the
concentration field to the correct unit
represented in the transport equations. Decoupling
changes the concentration field to the form of
the vertical diffusion, chemistry, aerosol, and
cloud process equations. .
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CCTM Classes and Their Default Module Classes
Default Module Process Analysis pa Process
Analysis is a diagnostic tool that can be used to
quantify the relative contribution of individual
science processes to species concentrations
predicted by the CCTM. The rates of change in
concentration due to individual processes or
factors affecting the species concentration (e.g.,
advection, diffusion, emissions, etc.) and
individual chemical reactions are integrated
over a prescribed time period. These integrated
rates provide a direct measure of the relative
effect of individual science processes as
simulated by CCTM. The integrated
chemical reaction rates can also be used to
elucidate important chemical characteristics of
the reacting system, such as the hydroxyl radical
and nitric oxide chain lengths. Both types of
information can be particularly useful in
understanding the difference in model predictions
that arise from changes in the model inputs or
individual components.
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On-Line Modeling
Off-Line Modeling
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Comparison of On-line and Off-line Modeling
Paradigms
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Comparison of On-line and Off-line Modeling
Paradigms
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Ideal One-Atmosphere Modeling
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Conclusion

• CMAQ is ready for combined one-atmosphere
  modeling
• convenient chemistry capability
• comprehensive process simulation
• versatile coding structure data handling
• maintains dynamic consistency
• uses generalized coordinates
• handles mass consistency problems

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Conclusion
Multiscale Capability

• Governing diffusion eq. in a generalized
  coordinates
• Conformal map projections
• Flexible vertical coordinate system
• Matching dry deposition algorithms
• Flux-form atmospheric diffusion and advection
• Schemes to maintain dynamic consistency
• Nesting techniques
• Subgrid scale modeling plume-in-grid

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The End.

• Have a Nice Training !