Shawn J. RoselleNOAA Atmospheric Science Modeling Division
In partnership with the U.S. Environmental Protection Agency
Research Triangle Park, NC
CMAQ Model Development: Current Model Configuration
and Future Plans
ACCENT-CMAS Training Workshop on Air Quality Modeling, Sofia, BulgariaAugust 6, 2006
Summary
• Background on modeling
• Current model features
• New developments on the horizon
Background
Role of Models in the Air Quality Planning Process
• Air quality modeling is a major part of the United States’ implementation of the National Ambient Air Quality Standards (NAAQS) for ozone and PM2.5
• State-of-science models are needed in the State Implementation Plan (SIP) process
Models are Central to the Air Quality Planning Process (cont.)
• Multi-pollutant capabilities O3, PM, acid/nutrient deposition, regional haze, air
toxics, Hg
• Multi-scale capabilities Synthesize scale interactions between continental/
regional/ urban
• Models are the only predictive tools to estimate emissions growth/change and the impacts of potential emissions control strategies on future-year air quality
Categories of Air Quality Models• Dispersion models (traditional)
Steady-state Gaussian models
• Receptor-oriented models Diagnostic; not predictive Provide data to indicate primary source
categories affecting a receptor
• Source-oriented models Predictive, as well as diagnostic Lagrangian or Eulerian frames of reference
grid cell
CMAQ Modeling System
SMOKE
Anthro and Biogenic Emissions processing
Fifth Generation Mesoscale Model (MM5)
or
Weather Research and Forecast Model (WRF)
CMAQ AQ Model-
Chemical-Transport Computations
Met-Chem Interface Processor (MCIP)
Met. data prep
NOAA Weather Observations
EPA Emissions Inventory
Hourly 3-D Gridded Chemical Concentrations
grid cell
36-km MM5165 x 129 x 34
36-km CMAQ148 x 112 x 14
12-km MM5202 x 208 x 34
12-km CMAQ199 x 205 x 14
Domains for Annual Simulations
Meteorology
• Penn State/NCAR Mesoscale Model-Gen. 5 (MM5) – community meteorology model Principally used as a weather forecast
model• MM5 is widely used in air quality community
– Emphasis on processes important for air quality– Four-dimensional data assimilation (FDDA)
» Resulting fields: model+observations
• Weather Research and Forecast (WRF) is the successor model to MM5
Sample MM5 Output (36-km grids)MM5 Winds and Precipitation
12 UTC 22 July 1998120-h simulation
“Daily Weather Map” courtesy of NOAA
Meteorology (cont.)
• ASMD meteorological model research Land-surface modeling (Pleim-Xiu model) Planetary Boundary Layer (PBL) processes Linkage between meteorology/chemistry
models (MCIP) Four-dimensional data assimilation (FDDA
in MM5) NOAA’s Weather Research and Forecast
(WRF) model testing and adaptation to CMAQ model system
Emissions
• Sparse Matrix Operator Kernel Emissions (SMOKE) system Includes emissions from point, area, mobile,
and natural sources
• R&D for meteorologically-dependent emissions VOCs from vegetation and NOx from soils
(BEIS3) Sea salt via wind/wave action Wildland fires and prescribed burns Blowing dust / agricultural sources of NH3
Solves atmospheric transport-diffusion equations, with chemistry, aerosols, and other relevant processes
Time-splitting of science processes
tzyxp
i
tzyx
i
t
c
t
c
,,,,,,
Community Multiscale Air Quality (CMAQ) Model
where i = chemical speciesx,y,z = 3-D space coordinatest = timep = processes
Emissions
CloudsClouds
Chemistry, AerosolsChemistry, Aerosols
Horizontal transport and diffusion
Vertical transport and diffusion
Plume-in-grid
CMAQ Response to Emissions Changes
CMAQ Response to Emissions Changes
CMAQ Model (cont.)
• Current Research Vertical diffusion
• Boundary layer turbulence– Asymmetric Convective Model v2
Deposition• Surface fluxes; land-surface modeling• Evaluation with flux field measurements
Plume-in-Grid• Sub-grid plume descriptions
Numerical algorithms• High performance computing
• Gas-phase Chemistry Chemical kinetic mechanisms
• Carbon Bond (CB) series• Statewide Air Pollution Research Center
(SAPRC) series• Mechanism adaptation and development of
efficient numerical solvers
CMAQ Model (cont.)
CMAQ Model (cont.)
• Aerosols Modal Approach Thermodynamic gas/aerosol partitioning Nucleation, condensation, coagulation Heterogeneous chemistry Secondary organic aerosol production Inorganic aerosol chemistry
AitkenAccumulation
Coarse
H2SO4
CMAQ Model (cont.)
COARSE MODE
NO3-
NH4+
SO4=
Na+
Cl-
H2O
POA
SOAa
SOAb
EC
Other
SVOCs
HNO3
NH3
H2O
Na+, Cl-, SO42-
Soil, Other
2 FINE MODES
Aromatics
Monoterpenes
HCl
• Trimodal size distribution• Aitken (0-0.1 µm), Accumulation(0.1-2.5 µm), and Coarse
• Gas/particle interactions treated for fine modes only – ISORROPIA instantaneous equilibrium
• Fine-modes coagulate
• Coarse mode, fine EC (black) & other fine PM (brown) are inert
Binkowski and Roselle, JGR, 2002
Chemical Species
Gases Particles NO2 CO PAN NH3 ASO4I AECJ
NO FORM ROR UMHP ASO4J A25I
O3 ALD2 NTR ANH4I A25J
O OLE FACD ANH4J ACORS
NO3 ETH AACD ANO3I ASEAS
O1D TOL CRES ANO3J ASOIL
OH XYL TO2 AORGPAI NUMATKN
HO2 ISOP OPEN AORGPAJ NUMACC
N2O5 PAR CRO AORGBI NUMCOR
HNO3 C2O3 MGLY AORGBJ AH2OI
HONO XO2 ISPD AORGAI AH2OJ
H2O2 XO2N SO2 AORGAJ DCV_Mie
PNA PACD SULF AECI EXT_Mie
VOCs
PM2.5
Recent chemical additions
• Air toxics – 20 species in gas phase
– Adding more toxics, including metals, semivolatiles, other Hazardous Air Pollutants (HAPs)
• Atmospheric mercury– Modifications include new cloud/aqueous phase chemistry
and gas phase reactions– CMAQ-Hg: first public release - March 2006
acetaldehyde carbon tetrachloride
ethylene oxide propylene dichloride
acrolein chloroform formaldehyde quinoline
acrylonitrile 1,3-dichloropropene
methylene chloride tetrachloroethane
1,3-butadiene ethylene dibromide napthalene trichloroethylene
benzene ethylene dichloride perchloroethylene vinyl chloride
Two CMAQ Development Tracks
• Community version Annual public releases (via CMAS) Designed for retrospective modeling for
policy and research Multiple configurations
• Air Quality Forecasting Operational Ozone and PM forecasts Integrated with NCEP forecast systems Single optimized configuration
Synergistic DevelopmentCommunity release AQF system
Faster gas-phasechemical solver (EBI)
Aerosol model upgradesAnd efficiency improvements
Modified minimum Kz
Mass conservation scheme
Modified cloud cover and convective cloud transport
New online photolysis model(work in progress)
CB05 Chemical Mechanism
Recent CMAQ Public Releases
• September 2000: CMAQv4.0• February 2001: CMAQv4.1• June 2002: CMAQv4.2.1• May 2003: CMAQv4.2.2• September 2003: CMAQv4.3• October 2004: CMAQv4.4• September 2005: CMAQv4.5• March 2006: CMAQv4.5.1
CMAQv4.5 & v4.5.1 Highlights
• Aerosols Added sea salt (fine equilibrium; non-interactive coarse mode) Updated ISORROPIA to v1.5
• Also recomputed tabulated binary activity coefficients Updated aerosol dry deposition algorithm
• Chemistry Added CB4/chlorine chemistry and associated EBI solver Added CB4/air toxics and SAPRC99/air toxics chemistry and
associated EBI solvers Beta-version of CB05 Added degradation algorithm to the generalized solvers
• Mercury Added mercury modeling capability
Chemical Mechanisms: CMAQv4.5.1
CMAQv4.5 & v4.5.1 Highlights (continued)
• Advection New mass conservation scheme using vertical velocities
derived from mass continuity• PBL modeling
New minimum Kz based on % urban land-use• Clouds
New sub-grid cloud mixing algorithm: vertical mixing algorithm based on Asymmetric Convective Model (ACM)
Aqueous Chemistry• Discontinued aerosol species lumping--separated elemental
carbon from primary aerosol; split organic aerosols into primary, secondary biogenic, and secondary anthropogenic
• Plume-in-Grid Capability for more frequent plume releases
CMAQv4.5 & v4.5.1 Highlights (continued)
• Dynamic allocation of vertical layers Enables same executable to be used for different vertical
grid configurations
• Parallel I/O Added worker and I/O processors partition scheme
• Diagnostic Tools Sulfate and primary carbon tracking Process Analysis
• Updated for latest version of model processes
• MCIP Add capability for WRF-ARW Dry dep. velocities for chlorine and mercury
Notes:• TCDiesel ≈ 5 × TCGasoline
• Both source categories track population density
Diagnostic Tools – Carbon Tracking
Fine Carbon from Diesel Exhaust Fine Carbon from Gasoline Exhaust
Notes:• TCBiomass is dominated by wildfires• TCFood tracks population density
TC2.5 from Biomass Combustion TC2.5 from Food Cooking
Diagnostic Tools – Carbon Tracking
Diagnostic Tools – Sulfate Tracking
All scales represent the fraction of total aerosol sulfate.
CMAQv4.6 Features
Model Upgrades for 2006
• Aerosols Updated ISORROPIA to v1.7
• Includes correction in activity coefficients for temperatures other than 298 K
• Ammonium nitrate aerosol concentrations increase somewhat
Revised to use T, RH-dependent “gamma” (heterogeneous N2O5 reaction probability) from Evans & Jacob (2005)
• Net production of nitrate decreases in the winter and increases slightly in the summer
Upper limit set for the RH input to ISORROPIA (95%)• Sets limits on the aerosol water concentrations
– Previous versions of CMAQ could have water concentrations as high as 1000 ug/m3
Updated parameters in the aerosol diagnostic file
• Chemistry New Carbon Bond (CB05) mechanism and
associated EBI solver• Summer ozone concentrations are about 8% higher
compared with the CB4 mechanism Include the gas-phase reactions involving N2O5
and H2O• Increases aerosol nitrate concentrations
Removed obsolete mechanism combinations (e.g. gas+aerosols w/o aqueous)
• Carbon Apportionment and Sulfate Tracking Added capability for CB05 (and AE4) mechanisms
CMAQv4.6 Upgrades (cont.)
Chemical Mechanisms: CMAQv4.6
CMAQv4.6 Upgrades (cont.)
• PBL modeling New ACM2: combined non-local and local closure
scheme• Produces different vertical profiles of pollutants in the
convective boundary layer (CBL)• Effective CBL mixing layer is shallower than for EDDY• Ground-level O3 concentrations slightly higher,
especially in the late afternoon• Precursors emitted at ground level tend to have lower
concentrations with more well mixed profiles in the CBL• Little effect on ground-level aerosol concentrations
• Plume-in-Grid Capability for AE4 mechanisms
CMAQv4.6 Upgrades (cont.)
• Circular buffer CGRID state file Write restart file
• Permits flexibility in the “CONC” file (write subset of species and layers)
• Parallel I/O Various updates (new version required for
CMAQv4.6 compilation)
Release Schedule
• CMAS will release CMAQv4.6 to the public in September/October 2006 Science description of new features Will include a model evaluation report Test datasets
Future Work
• Develop on-line coupling capability for WRF-CMAQ Allow aerosol feedback to radiation model Closer temporal coupling between
meteorology and chemistry Integrated resolved-scale microphysics and
aqueous chemistry Aerosol effects on microphysics
Work in progress
Work in progress (cont.)
• Aerosols Gas-phase interactions with coarse-mode sea salt Incorporate a new SOA module for oxidation of
aromatic, isoprene, and monoterpene mixtures
• Photolysis New in-line photolysis model for CMAQ
• Hybrid of TUV (Madronich) and Fast-J (Prather)• 7 wavelength bands in UV and visible• Updated absorption cross-sections and quantum yields• Includes extinction and scattering by CMAQ aerosols• Effects of clouds will be added to on-line calculations
• Cloud modeling Collaboration with NOAA to adapt WRF/CHEM
convective cloud model for CMAQ • CMAQ aqueous chemistry module• Wet deposition
Generalized aqueous chemistry solver• Develop operational satellite assimilation for
Surface insolation Photolysis rates Skin temperature nudging for soil moisture Cloud dynamics
Work in progress (cont.)
CMAQ Model Limitations
• Errors/uncertainties in input data Initial and boundary conditions Meteorology Emissions
• Gaps or incomplete understanding in process details or mathematical representations (e.g. VOC chemistry modeled using a lumped mechanism)
CMAQ Model Limitations (cont.)
• Issues of horizontal scale Regional through urban modeling domains
• Typical grid cell sizes: 1-40 km Scale-dependent process parameterizations
• For grid cell sizes >40 km:– Grid averaging can significantly affect results– Misrepresentation of emissions/chemistry at this scale
• For grid cell sizes <1 km:– Resolving explicit atmospheric turbulence– Model parameterizations break down– Requires different modeling approaches
(e.g. LES, CFD)
Concluding Remarks
• CMAQ and similar models are required tools for air quality planning
• Such air quality models represent a complex atmospheric system, with uncertainties in each system component Research is conducted using the models as
“numerical laboratories”, in conjunction with laboratory and field data, to reduce the component uncertainties
Concluding Remarks (cont.)
• Modeling applications Regulatory assessments of O3, PM2.5,
air toxics, mercury Acid/nutrient deposition AQ/climate interactions
Acknowledgements
DisclaimerDisclaimer: The research presented here was performed under the : The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce’s National Oceanic and Agency (EPA) and the U.S. Department of Commerce’s National Oceanic and Atmospheric Administration (NOAA) and under agreement number Atmospheric Administration (NOAA) and under agreement number DW13921548. This work constitutes a contribution to the NOAA Air Quality DW13921548. This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their views or policies.publication, it does not necessarily reflect their views or policies.
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