CMAQ Tagged Species Source Apportionment (TSSA)
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Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CMAQ Tagged Species Source Apportionment (TSSA) Gail Tonnesen, Bo Wang et al., Air Quality Modeling Group University of California, Riverside WRAP Attribution of Haze Meeting, Denver, CO July 22, 2004
description
CMAQ Tagged Species Source Apportionment (TSSA). Gail Tonnesen, Bo Wang et al., Air Quality Modeling Group University of California, Riverside WRAP Attribution of Haze Meeting, Denver, CO July 22, 2004. Need to understand which emissions sources contribute to haze and other pollutants. - PowerPoint PPT Presentation
Transcript of CMAQ Tagged Species Source Apportionment (TSSA)
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
CMAQ Tagged Species Source Apportionment (TSSA)
Gail Tonnesen, Bo Wang et al.,
Air Quality Modeling Group
University of California, Riverside
WRAP Attribution of Haze Meeting, Denver, CO July 22, 2004
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Motivation
• Need to understand which emissions sources contribute to haze and other pollutants.
• Use this information to assist in developing control strategies.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Modeling Approaches for Source Apportionment
• Chemical Mass Balance analysis
• Back-trajectory models
• Lagrangian models
• Sensitivity Studies
• Mass tracking approaches.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Sensitivity Methods (1)
1. Run a model Base Case simulation.
2. Add-in or Zero-out a particular source and run a the model again.
3. The difference in the base case and the sensitivity case predicts the effect of changing that source on concentration at all receptor sites.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Sensitivity Methods (2)
• Advantages of Sensitivity Methods:– directly related to development of control measures.– Conceptually simple to apply.
• Problems with Sensitivity Methods:– Brute force approaches (removing one species in each
model run) are computationally expensive.– Sensitivity results depend on the base case scenario.– Sensitivities results can be non-linear and non-additive.– CMAQ exhibits numerical noise in PM sensitivity runs.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Sensitivity Methods (3)
• Decoupled Direct Method is a computationally efficient sensitivity method:– Calculates many sensitivities in one run.– Difficult to implement in PM models.– Calculates derivative – but sensitivities can be
non-linear.
• Recommendation: Sensitivity studies are a valuable tool, but expensive to apply, and care is needed in interpretation of results.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Mass Tracking Methods
• Mass Tracking Algorithms– Output and analyze mass flux terms and
chemical reaction rates for each grid cell.– Computationally prohibitive.
• OSAT– Uses tracers to track O3 formation that was
sensitive to VOC or NOx.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Tagged Species Approach (1)
• Use “Tagged Species” or Tracers to track chemical transformations and transport of each PM species or PM precursor .
• Add the tracers for key species and for defined source regions & source categories.
• Provides 3-D fields showing source attribution of of PM species for any grid cell in model domain.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Tagged Species Approach (2)
• Method: Add one new set of tagged species for each emissions source category or source location being tracked.– Straight forward for non-reactive species: add 1 tracer
for each source.– Example: in each grid cell the sum of all tracers for EC
equals the total (bulk) EC concentration in each cell.– Each tracer is defined for all grid cells and is emitted,
transported, and removed proportional to its weight of the bulk species in each grid cell.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Tagged Species Approach (3)
• More complicated for chemical reactive species and secondary particulates:– Must also track the chemical reactions that convert a
tracer between different gas species and from gas to PM.– Model include approximately 6 forms of N species, must
carry 6 additional tracers for each NOx source category to track the contributions to aerosol nitrate.
– SOA formation is still more complex, not included in current algorithm.
– SO4 and other PM species are easier and less computational expensive to treat.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
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92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 70 70 70 70 70
92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 70 70 70 70 70
92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 70 70 70 70 70
92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 70 70 70 70 70 70
92 92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 70 0 70 70 70 70 0
92 92 92 92 92 92 60 60 60 60 92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 60 60 92 92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 60 60 60 60 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 60 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 60 60 60 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 60 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
91 91 91
0 0 0
0 0 0
0 0 0
0 0 0
44 0 0
44 44 0
44 44 44
44 44 44
33 44 44
33 33 44
33 33 33
33 33 33
33 33 33
33 33 33
33 33 33
33 33 33
33 33 33
33 33 33
33 33 33
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
59 59 59
75 59 59
75 75 59
75 75 59
75 75 75
75 75 75
80 75 65
80 75 65
80 80 65
80 65 65
80 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
99 99 99
70 70 70
70 70 70
70 70 70
70 70 70
70 70 70
70 70 70
0 70 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
Source Area Mapping File: Each state is distinguished by a unique number
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Traced Source TagsTypes Source Category Notes
ICON ICON Initial Concentration
BCON BCON Boundary Concentration
Emissions MV_* Mobile sources of any state
BG_* Biogenic sources of any state
RD_* Road dust of any state
NR_* Non- Road dust of any state
PN_* Point sources without SO2 of any state
PS_* Point sources with SO2 of any state
AR_* Area sources of any state
WF_* WF Fire of any state
AG_* AG Fire of any state
RX_* RX Fire of any state
MX_* Mexico Fire
ET_* Total Emission of any state
*_WRAP Any type of emission of WRAP domain
Others OTHERS Any sources other than all of the above
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Transport & Loss Terms• Advection
– Calculate mass flux between grid cells to update tracers.
• Vertical Diffusion– Apply the CMAQ diffusion algorithms to tracers.– Also evaluate new algorithms to estimate actual 2-way mass
transfer between layers.
• Update for mass flux in CLOUD & aqueous chemistry algorithm.
• Update tagged species for emissions and deposition terms.• Check for mass conservation at each step and adjust mass
if needed. Halt if large errors.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
TSSA Structure Design driver.F:
read tssa configuration, ptssa_init …
do n = 1, nsteps
tssa_couple
tssa_decouple
write tssa output
end do
sciproc.F
Xadv
Yadv
Yadv
Xadv
Zadv
Tssa Adjadv
Hdiff
Tssa Decouple
Vdiff
Tssa Cldproc
Chem
Tssa Aero
Tssa Couple
Hppm
Tssa adv update
vppm
Tssa hdiff update
Tssa vdiff update
smvgear Tssa chem update
TSSA mass normalization
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Tagged Species for Nitrates
• NOX = reactive N family.= { NO, NO2, NO3, 2*N2O5, HONO, PNA}
• HNO3• PAN• RNO3• ANO3J• ANO3I
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Chemical Transformations
• Emissions are as NOx = NO + NO2 • Use integrated reaction rates at each time step
to update the tagged species:– NOX PAN
– NOX RNO3
– NOx HNO3
– HNO3 ANO3
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Implementation in CMAQ
• Previously implemented in CMAQ v4.2.2. (12/03)
• Currently implemented in CMAQ v4.4
• Programming Language: Fortran 90
• Compilers: pgf90 or intel fortran compiler (ifc)
• Parallelism: supports multi-processor usage (MPI)
• Currently implemented with GEAR & QSSA chemistry solvers.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Output Formats
• 3-d concentration field for each tagged species– Each model grid cell is included as a receptor.– Results can be viewed as 3-d animation of the
tagged species, or layer 1 animations in PAVE– Bar plots for receptor showing attribution is most
useful for the receptor sites.
• Output files for annual simulation are too large with over 12 GB per day.– Currently outputting only layer 1.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Computational Cost/Constraints
• Slower run time because we use GEAR or QSSA chemistry (about 4x cost of EBI solver).
• RAM memory is primary constraint:– For many tracers we split them between 2 model
runs to avoid paging memory to disk.
• Run Time: about 3 hours per day using 8 Opteron CPUs with 2 GB RAM.
• With 32 CPUs, running CMAQ in 4 seasons, takes about 2 weeks for an annual simulation.
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Animation gifs demo:
Center for Environmental Research and Technology/Air Quality Modeling
University of California at Riverside
Future Work
• Test alternate treatments of HNO3 NO3 and H2SO4 SO4 equilibrium.
• Implement organic aerosols and ozone.• Improve Graphics/Statistics Program to automate
Tracer Result Evaluation.• More Testing- comparisons with CAMx PSAT runs,
and testing for mass conservation.• Scalability in supporting other modeling domains
– Create corresponding source area mapping files
– county domains.
