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Outline Regulatory modeling Source attribution: apportionment & sensitivity Lateral boundary inflow attribution project References
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Photochemical grid model estimates of lateral boundary
contributions to ozone and particulate matter across the
continental United States Kirk Baker U.S. Environmental Protection
Agency Research Triangle Park, NC January 6, 2016 Outline
Regulatory modeling
Source attribution: apportionment & sensitivity Lateral
boundary inflow attribution project References Regulatory Modeling
Use regional to local scale photochemicaltransport models (CMAQ
& CAMx) Typically use 12 km grid res., sometimes 4 km,not
coarser than 12 km for a regulatoryassessment 2011 NEI based
emissions O3 & PM2.5 NAAQS review cycle Interstate transport
rules: NOX SIP Call, CAIR,CSASPR, etc. NESHAP sector rules such as
Mercury & AirToxics (MATS) New Source Review/Prevention of
SignificantDeterioration: single source permit modelingfor O3 &
secondary PM State/local agencies: NAAQS attainment,Regional Haze
rule progress Mobile source sector rules Other types of assessments
usingregulatory quality modeling but notnecessarily for
rulemakings: National Air Toxics Assessment 2011 Source Sensitivity
& Apportionment Modeling Approaches
How will the modeled concentrations change based on changes to
emissions? Source sensitivity approaches Brute force zero out or
emissions perturbations Decoupled Direct Method (DDM) What are the
various contributors to modeled concentrations? Source
apportionment approaches Ozone and PM source apportionment (OSAT,
PSAT, ISAM) (Kwok et al 2013; Kwok et al, 2015; ENVRION,2015)
Tracers: inert or reactive *All techniques have strengths and
limitations Source Sensitivity & Apportionment Examples
Source groups may be single sources, groups of sources (e.g.
sector, biogenics, lateralboundary inflow), entire Counties, entire
States, entire Countries Baker and Kelly, 2014 Lateral boundary
attribution: motivation
Increasing interest in characterizing the contribution from
chemicallateral boundary inflow (Dolwick et al, 2015) Compare
chemically reactive and non-reactive tracer approaches
forestimating lateral boundary inflow contribution to O3 and PM2.5
Illustrate the strengths and weaknesses of the various approaches
Are any techniques efficient enough to be part of routine
modelapplication More project details available in Baker et al,
2015 Background All assessments 12km annual 2011 CAMx
platform
CB6r2 gas chemistry; ISORROPIA inorganic chemistry GEOS-CHEM
chemical inflow Surface to 50 mb with 25 layers O3 boundary
contribution estimated using multiple techniques Reactive tracers:
Ozone Source Apportionment Technology (OSAT) withstratified
boundaries (west, north, east, south, top) uses reactive
tracersthrough all chemical and physical processes in the model
Reactive tracers: RTRAC with stratified boundaries (west, north,
east,south) with the west and north boundaries further stratified
by layers: 1 to14, 15 to 22, and 23 to 25 Non-reactive tracers:
boundary condition only run (no chemistry) 7/8/2015 Background All
assessments 12km annual 2011 CAMx platform
CB6r2 gas chemistry; ISORROPIA inorganic chemistry GEOS-CHEM
chemical inflow Surface to 50 mb with 25 layers PM2.5 boundary
contribution to PM2.5 sulfate, nitrate, ammonium, EC,
primarycomponent of OC, and other primarily emitted PM2.5 Reactive
tracers: Particulate Source Apportionment Technology (PSAT)
withstratified boundaries (west, north, east, south, top)
Non-reactive tracers: boundary condition only run (no emissions
orchemistry) 7/8/2015 Reactive Tracers: OSAT, RTRAC/RTCMC
The CAMx reactive tracer (RTRAC) probing tool providesa flexible
approach for introducing gas and particulatematter tracers within
CAMx simulations; can not be runat the same time as OSAT/PSAT Each
RTRAC tracer is influenced by boundary conditions,advection,
diffusion, emissions and dry deposition. Gas-phase tracers can also
undergo chemical destructionand/or production using either a
simpler (RTRAC) ormore complex (RTCMC) chemistry interface. The
RTRAC Chemical Mechanism Compiler (RTCMC)allows the user to
externally define a full chemistrymechanism with no limits on
complexity (withinavailable computer resources). 7/8/2015 RTCMC
Template for CB6r2 provided by ENVIRON
Example input chemistry control file for 2 sets ofextra O3
destruction reactions for the boundarytracking simulation The
configuration for this project does not accountfor NO titration A
total of 8 additional sets of tracers were used totrack 3 separate
vertical layers on the west andnorth boundaries and full faces east
and south Additional RTCMC input is a second ICON andBCON file that
only contains tracer concentrations(e.g. O3A, O3B, etc.) Fortran
program to manipulate ICBC input files forRTCMC provided by ENVIRON
No attempt to apply RTCMC for PM boundarycontributions 7/8/2015 O3
Contribution Monthly average O3contribution fromthe west
lateralboundary using theOSAT approach. Surface level. O3
Contribution Monthly average O3contribution fromthe north
lateralboundary using theOSAT approach. Surface level. Method
Comparison Monthly average O3 contributionfrom all lateral
boundaries usingOSAT (left panels), the difference inmonthly
average O3 contributionusing inert tracers (middle panels)and the
RTRAC approach (rightpanels). Surface level. Cool colors in the
difference plotsindicate OSAT estimates are higherand warm colors
indicate thealternative approach estimates arehigher. Inert and
RTRAC tend to have largerlateral boundary O3 contributionthan OSAT
reactive tracer approach Method Comparison Scatter density plots
showing hourlymodel estimated lateral boundarycontribution methods
compared atCASTNET monitor locations: OSATand inert tracers (top
left), OSAT andRTRAC (top right). Hourly model estimated bulk
O3compared with estimated lateralboundary contribution from
theinert tracers (bottom left) and OSAT(bottom right) approaches
atCASTNET locations. Colors represent the percentage ofpoints
falling at each location on theplot so warm colors indicate
areaswith a large amount of values. Western boundary inflow (RTRAC)
Northern boundary inflow (RTRAC)
Layers 1-14 (left); (mid); (right) Northern boundary inflow (RTRAC)
Layers 1-14 (left); (mid); (right) *results shown above are surface
level PM2.5 Contribution Monthly average PM2.5contribution from all
lateralboundaries and the modeltop using the PSATapproach. Surface
level. Contribution tracked fromeach lateral face, justshown in
aggregate herefor brevity. IMPROVE PM2.5 Bias (model estimate
measured estimate) paired in time and space with modeled
contribution from lateral boundary inflow using the PSAT approach.
Only IMPROVE sites shown. CASTNET O3 Hourly bias (model estimate
measuredestimate) paired in time and space withmodeled contribution
from lateral boundaryinflow using the OSAT approach. Only model
estimates of ozone where thelateral boundary contribution is
greater than90% of the bulk modeled O3 are shown. Bias greater than
zero indicates a model over- prediction of baseline ozone and below
zeroindicates a model under-prediction ofbaseline ozone. Colors
represent the percentage of pointsfalling at each location on the
plot so warmcolors indicate areas with a large amount ofvalues. No
obvious spatial patterns in bias Concluding Remarks Inert tracers
do not provide aphysically realistic contributionestimate for ozone
Better ways of evaluating theboundary inflow? This type
ofassessment misses the situationswhere observed BCONinfluence is
not captured due tomischaracterized meteorology OSAT more
computationallyefficient than RTRAC approach Not clear any approach
efficientenough for routine application References Baker, K.R.,
Emery, C., Dolwick, P., Yarwood, G., Photochemical grid model
estimates oflateral boundary contributions to ozone and particulate
matter across the continental UnitedStates. Atmospheric Environment
123, Dolwick, P., Akhtar, F., Baker, K.R., Possiel, N., Simon, H.,
Tonnesen, G., Comparison ofbackground ozone estimates over the
western United States based on two separate modelmethodologies.
Atmospheric Environment 109, Kwok, R., Baker, K.R., Napelenok, S.,
Tonnesen, G., Photochemical grid modelimplementation of VOC, NO x,
and O 3 source apportionment. Geoscientific Model Development8,
Baker, K.R., Kelly, J.T., Single source impacts estimated with
photochemical model sourcesensitivity and apportionment approaches.
Atmospheric Environment 96, Kwok, R., Napelenok, S., Baker, K.R.,
Implementation and evaluation of PM2.5 sourcecontribution analysis
in a photochemical model. Atmospheric Environment 80, ENVIRON, CAMx
Users Manual.