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
1
Outline
• Regulatory modeling
• Source attribution: apportionment & sensitivity
• Lateral boundary inflow attribution project
• References
2
Regulatory Modeling
• Use regional to local scale photochemical
transport models (CMAQ & CAMx)
• Typically use 12 km grid res., sometimes 4 km,
not coarser than 12 km for a regulatory
assessment
• 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 & Air
Toxics (MATS)
 New Source Review/Prevention of Significant
Deterioration: single source permit modeling
for O3 & secondary PM
 State/local agencies: NAAQS attainment,
Regional Haze rule progress
• Mobile source sector rules
• Other types of assessments using
“regulatory” quality modeling but not
necessarily for rulemakings:
 National Air Toxics Assessment 2011
3
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
4
Source Sensitivity & Apportionment Examples
• Source groups may be single sources, groups of sources (e.g. sector, biogenics, lateral
boundary inflow), entire Counties, entire States, entire Countries…
Baker and Kelly, 2014
5
Lateral boundary attribution: motivation
• Increasing interest in characterizing the contribution from chemical
lateral boundary inflow (Dolwick et al, 2015)
• Compare chemically reactive and non-reactive tracer approaches for
estimating 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 model
application
• More project details available in Baker et al, 2015
6
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) with
stratified boundaries (west, north, east, south, top) uses reactive tracers
through 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 to
14, 15 to 22, and 23 to 25
• Non-reactive tracers: boundary condition only run (no chemistry)
7/8/2015
Layer
25
24
23
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Sigma
0
0.1
0.2
0.3
0.4
0.5
0.6
0.65
0.7
0.74
0.77
0.8
0.82
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0.97
0.98
0.99
0.995
0.9975
Height (m)
17,556
12,822
10,002
7,932
6,275
4,885
3,683
3,136
2,619
2,226
1,941
1,665
1,485
1,308
1,134
964
797
632
470
311
232
154
77
38
19
7
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, primary
component of OC, and other primarily emitted PM2.5
• Reactive tracers: Particulate Source Apportionment Technology (PSAT) with
stratified boundaries (west, north, east, south, top)
• Non-reactive tracers: boundary condition only run (no emissions or
chemistry)
7/8/2015
Layer
25
24
23
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Sigma
0
0.1
0.2
0.3
0.4
0.5
0.6
0.65
0.7
0.74
0.77
0.8
0.82
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0.97
0.98
0.99
0.995
0.9975
Height (m)
17,556
12,822
10,002
7,932
6,275
4,885
3,683
3,136
2,619
2,226
1,941
1,665
1,485
1,308
1,134
964
797
632
470
311
232
154
77
38
19
8
Reactive Tracers: OSAT, RTRAC/RTCMC
• The CAMx reactive tracer (RTRAC) probing tool provides
a flexible approach for introducing gas and particulate
matter tracers within CAMx simulations; can not be run
at 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 destruction
and/or production using either a simpler (RTRAC) or
more complex (RTCMC) chemistry interface.
• The RTRAC Chemical Mechanism Compiler (RTCMC)
allows the user to externally define a full chemistry
mechanism with no limits on complexity (within
available computer resources).
7/8/2015
Ozone Source Reactive
Apportionment Tracers
(OSAT)
(RTCMC)
Yes
Yes
O3 photolysis to O( 1D)
Yes
No
O3 removal by NO
Yes
Yes
O3 removal by HOx
Yes
Yes
O3 removal by isoprene
and terpenes
Photolysis
Yes
Yes
Wet Deposition
Yes
No
Dry Deposition
Yes
Yes
Inert
Tracer
No
No
No
No
No
Yes
Yes
9
RTCMC
• Template for CB6r2 provided by ENVIRON
• Example input chemistry control file for 2 sets of
extra O3 destruction reactions for the boundary
tracking simulation
• The configuration for this project does not account
for NO titration
• A total of 8 additional sets of tracers were used to
track 3 separate vertical layers on the west and
north boundaries and full faces east and south
• Additional RTCMC input is a second ICON and
BCON file that only contains tracer concentrations
(e.g. O3A, O3B, etc.)
• Fortran program to manipulate ICBC input files for
RTCMC provided by ENVIRON
• No attempt to apply RTCMC for PM boundary
contributions
7/8/2015
#Species,Type,Ambient,Tolerance,deposition vel,wet scav,mw
NO
A
1.000E-04
1.000E-08
1.500E-03
O
A
3.178E-10
1.000E-12
0.000E+00
NO3
A
6.836E-08
1.000E-12
0.000E+00
OH
A
1.683E-07
1.000E-12
0.000E+00
HO2
A
2.052E-05
1.000E-12
0.000E+00
XO2
A
1.485E-05
1.000E-12
0.000E+00
XO2N
A
1.175E-06
1.000E-12
0.000E+00
MEO2
A
1.649E-06
1.000E-12
0.000E+00
MEPX
A
2.516E-06
1.000E-12
2.000E-03
C2O3
A
2.378E-07
1.000E-12
0.000E+00
CXO3
A
1.819E-07
1.000E-12
0.000E+00
ISOP
A
1.500E-03
1.000E-08
1.000E-03
TERP
A
1.000E-03
1.000E-08
1.000E-03
O3A
F
1.000E-18
1.000E-08
-3.000E-03
O1DA
F
1.000E-18
1.000E-12
0.000E+00
HOXA
F
1.000E-18
1.000E-12
0.000E+00
O3B
F
1.000E-18
1.000E-08
-3.000E-03
O1DB
F
1.000E-18
1.000E-12
0.000E+00
HOXB
F
1.000E-18
1.000E-12
0.000E+00
#Equation ; Rate constants from CB6r2
001 [O3A]
-> [O1DA]
002 [O1DA] -> [O3A]
003 [O1DA] ->
004 [O3A] + [OH]
-> [HOXA]
005 [O3A] + [HO2]
-> [HOXA]
006 [HOXA] + [NO]
-> [O3A]
007 [HOXA] + [HO2]
->
008 [HOXA] + [HO2]
->
009 [HOXA] + [MEO2]
->
010 [HOXA] + [XO2]
->
011 [HOXA] + [XO2N]
->
012 [HOXA] + [C2O3]
-> (0.2) [O3A]
013 [HOXA] + [CXO3]
-> (0.2) [O3A]
014 [O3A] + [ISOP]
->
015 [O3A] + [TERP]
->
016 [O3B]
-> [O1DB]
017 [O1DB] -> [O3B]
018 [O1DB] ->
019 [O3B] + [OH]
-> [HOXB]
020 [O3B] + [HO2]
-> [HOXB]
021 [HOXB] + [NO]
-> [O3B]
022 [HOXB] + [HO2]
->
023 [HOXB] + [HO2]
->
024 [HOXB] + [MEO2]
->
025 [HOXB] + [XO2]
->
026 [HOXB] + [XO2N]
->
027 [HOXB] + [C2O3]
-> (0.2) [O3B]
028 [HOXB] + [CXO3]
-> (0.2) [O3B]
029 [O3B] + [ISOP]
->
030 [O3B] + [TERP]
->
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
;
0
5
15
2
2
2
19
20
2
2
2
2
2
2
2
0
5
15
2
2
2
19
20
2
2
2
2
2
2
2
0.000E+00
1.338E-09
1.284E-08
1.020E-10
1.218E-14
2.070E-10
1.320E-11
1.848E-32
2.280E-11
4.080E-11
4.080E-11
3.120E-11
3.120E-11
6.180E-13
7.200E-14
0.000E+00
1.338E-09
1.284E-08
1.020E-10
1.218E-14
2.070E-10
1.320E-11
1.848E-32
2.280E-11
4.080E-11
4.080E-11
3.120E-11
3.120E-11
6.180E-13
7.200E-14
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
0.00E+00
1.15E+02
0.00E+00
-9.40E+02
6.93E+02
2.70E+02
6.00E+02
2.80E+03
7.80E+02
8.00E+02
8.00E+02
9.80E+02
9.80E+02
-1.995E+03
-8.21E+02
0.00E+00
1.15E+02
0.00E+00
-9.40E+02
6.93E+02
2.70E+02
6.00E+02
2.80E+03
7.80E+02
8.00E+02
8.00E+02
9.80E+02
9.80E+02
-1.995E+03
-8.21E+02
30.0
16.0
62.0
17.0
33.0
1.0
1.0
47.0
48.0
75.0
75.0
68.0
136.0
48.0 O3
16.0
33.0
48.0 O3
16.0
33.0
4.57
1.140E-31
1.596E-52
9.80E+02
3.18E+03
4.57
1.140E-31
1.596E-52
10
9.80E+02
3.18E+03
O3 Contribution
• Monthly average O3
contribution from
the west lateral
boundary using the
OSAT approach.
• Surface level.
11
O3 Contribution
• Monthly average O3
contribution from
the north lateral
boundary using the
OSAT approach.
• Surface level.
12
Method Comparison
• Monthly average O3 contribution
from all lateral boundaries using
OSAT (left panels), the difference in
monthly average O3 contribution
using inert tracers (middle panels)
and the RTRAC approach (right
panels). Surface level.
• Cool colors in the difference plots
indicate OSAT estimates are higher
and warm colors indicate the
alternative approach estimates are
higher.
• Inert and RTRAC tend to have larger
lateral boundary O3 contribution
than OSAT reactive tracer approach
13
Method Comparison
• Scatter density plots showing hourly
model estimated lateral boundary
contribution methods compared at
CASTNET monitor locations: OSAT
and inert tracers (top left), OSAT and
RTRAC (top right).
• Hourly model estimated bulk O3
compared with estimated lateral
boundary contribution from the
inert tracers (bottom left) and OSAT
(bottom right) approaches at
CASTNET locations.
• Colors represent the percentage of
points falling at each location on the
plot so warm colors indicate areas
with a large amount of values.
14
Western boundary inflow (RTRAC)
Northern boundary inflow (RTRAC)
Layers 1-14 (left); 15-22 (mid); 23-25 (right)
Layers 1-14 (left); 15-22 (mid); 23-25 (right)
Layer
25
24
23
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
*results shown above are surface level
Sigma
0
0.1
0.2
0.3
0.4
0.5
0.6
0.65
0.7
0.74
0.77
0.8
0.82
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0.97
0.98
0.99
0.995
0.9975
Height (m)
17,556
12,822
10,002
7,932
6,275
4,885
3,683
3,136
2,619
2,226
1,941
1,665
1,485
1,308
1,134
964
797
632
470
311
232
154
77
38
19
15
PM2.5 Contribution
• Monthly average PM2.5
contribution from all lateral
boundaries and the model
top using the PSAT
approach.
• Surface level.
• Contribution tracked from
each lateral face, just
shown in aggregate here
for brevity.
16
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.
17
CASTNET O3
• Hourly bias (model estimate – measured
estimate) paired in time and space with
modeled contribution from lateral boundary
inflow using the OSAT approach.
• Only model estimates of ozone where the
lateral boundary contribution is greater than
90% of the bulk modeled O3 are shown.
• Bias greater than zero indicates a model overprediction of baseline ozone and below zero
indicates a model under-prediction of
baseline ozone.
• Colors represent the percentage of points
falling at each location on the plot so warm
colors indicate areas with a large amount of
values.
• No obvious spatial patterns in bias
18
Concluding Remarks
• Inert tracers do not provide a
• OSAT more computationally
physically realistic contribution
efficient than RTRAC approach
estimate for ozone
• Not clear any approach efficient
• Better ways of evaluating the
enough for routine application
boundary inflow? This type of
Appr. Time per Ratio per regular
assessment misses the situations Model Simulation
model day (mins)
simulation
Regular CAMx simulation
33
1
where “observed” BCON
No emissions or chemistry
11
0.3
40
1.2
influence is not captured due to OSAT (5 BC tracers + 1 other group)
RTCMC (5 tracers)
60
1.8
mischaracterized meteorology
RTCMC (8 tracers)
80
2.4
PSAT (5 BC tracers + 1 other group)
54
1.6
19
References
• Baker, K.R., Emery, C., Dolwick, P., Yarwood, G., 2015. Photochemical grid model estimates of
lateral boundary contributions to ozone and particulate matter across the continental United
States. Atmospheric Environment 123, 49-62.
• Dolwick, P., Akhtar, F., Baker, K.R., Possiel, N., Simon, H., Tonnesen, G., 2015. Comparison of
background ozone estimates over the western United States based on two separate model
methodologies. Atmospheric Environment 109, 282-296.
• Kwok, R., Baker, K.R., Napelenok, S., Tonnesen, G., 2015. Photochemical grid model
implementation of VOC, NO x, and O 3 source apportionment. Geoscientific Model Development
8, 99-114.
• Baker, K.R., Kelly, J.T., 2014. Single source impacts estimated with photochemical model source
sensitivity and apportionment approaches. Atmospheric Environment 96, 266-274.
• Kwok, R., Napelenok, S., Baker, K.R., 2013. Implementation and evaluation of PM2.5 source
contribution analysis in a photochemical model. Atmospheric Environment 80, 398-407.
• ENVIRON, 2015. CAMx Users Manual. www.camx.com.
20