Page 1
Comprehensive model evaluation of PM2.5 species over Japan: - Comparison among AERO5, AERO6, and AERO6-VBS models
The 13th Annual CMAS Conference, October 28, 2014
ー Contents ー 1. Introduction - PM2.5 in Japan / PM2.5 modelling
2. Methodology - Chemical transport models /
Observations
3. Results - Model evaluations
4. Summary ー Acknowledgement ーFunds : Environment Research and Technology Development Fund (5-1408, S12-1, 5B-1101)Technical support: K. Suto and T. Noguchi (NIES)
Yu Morino, Tatsuya Nagashima, Seiji Sugata, Kei Sato, Kiyoshi Tanabe,
Akinori Takami, Hiroshi Tanimoto, and Toshimasa Ohara National Institute for Environmental Studies, Japan
Page 2
Urban (N=12)Rural (N=5)Roadside (N=16)
PM2.5 in Japan
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
PM2.5 environmental standard
in Japan (Sept. 2009 ‒)
Annual mean: 15 μg m-3
Daily mean: 35 μg m-3
Temporal variations during 2001-2010
Ministry of Environment (2012)
PM2.
5 con
cent
ratio
ns
Ministry of Environment (2013)
PM2.5 standard was not attained in western Japan and Tokyo Metropolitan Area.
PM2.5 env. standard○ : Attained■▲ : Not-attained
Spatial variations in 2012
Attained
Unattained
1. Introduction
Page 3
PM2.5 modelling in Tokyo Metropolitan Area (in summer 2007)
Model intercomparison of PM2.5 species (Morino et al., JSAE, 2010)(CMAQ v4.7.1 and CMAQ 4.6 were used.)
All models significantly underestimated OA.
-1.0
-0.5
0.0
0.5
1.0
r (
(PM
2.5))
4321S1 S2 S3 S4
r ((PM2.5))
30
20
10
0
PM
2.5 (g
m-3
)
4321S1 S2 S3 S4
Mean (PM2.5)
Obs (TEOM)
-1.0
-0.5
0.0
0.5
1.0r
(NO
3- )
4321S1 S2 S3 S4
r (NO3-)
-1.0
-0.5
0.0
0.5
1.0
r (S
O42-
)
4321S1 S2 S3 S4
r (SO42-
)
-1.0
-0.5
0.0
0.5
1.0
r (O
A)
4321S1 S2 S3 S4
r (OA)
8
6
4
2
0
OA
(g
m-3
)
4321S1 S2 S3 S4
Mean (OA)
6
4
2
0
SO
42- (g
m-3
)
4321S1 S2 S3 S4
Mean (SO42-
)
Obs M1 M2 M3 M4
10
8
6
4
2
0
NO
3- (
g m
-3)
4321S1 S2 S3 S4
Mean (NO3-)
-1.0
-0.5
0.0
0.5
1.0
r (
(PM
2.5))
4321S1 S2 S3 S4
r ((PM2.5))
30
20
10
0
PM
2.5 (g
m-3
)
4321S1 S2 S3 S4
Mean (PM2.5)
Obs (TEOM)
-1.0
-0.5
0.0
0.5
1.0
r (N
O3- )
4321S1 S2 S3 S4
r (NO3-)
-1.0
-0.5
0.0
0.5
1.0
r (S
O42-
)
4321S1 S2 S3 S4
r (SO42-
)
-1.0
-0.5
0.0
0.5
1.0
r (O
A)
4321S1 S2 S3 S4
r (OA)
8
6
4
2
0
OA
(g
m-3
)
4321S1 S2 S3 S4
Mean (OA)
6
4
2
0
SO
42- (g
m-3
)
4321S1 S2 S3 S4
Mean (SO42-
)
Obs M1 M2 M3 M4
10
8
6
4
2
0
NO
3- (
g m
-3)
4321S1 S2 S3 S4
Mean (NO3-)
S1: Komae, S2: Kisai, S3: Maebashi, S4: Tsukuba
Org
anic
aer
osol
-1.0
-0.5
0.0
0.5
1.0
r (
(PM
2.5)
)
4321S1 S2 S3 S4
r ((PM2.5))
30
20
10
0
PM
2.5 (g
m-3
)
4321S1 S2 S3 S4
Mean (PM2.5)
Obs (TEOM)
-1.0
-0.5
0.0
0.5
1.0
r (N
O3- )
4321S1 S2 S3 S4
r (NO3-)
-1.0
-0.5
0.0
0.5
1.0
r (S
O42-
)
4321S1 S2 S3 S4
r (SO42-
)
-1.0
-0.5
0.0
0.5
1.0
r (O
A)
4321S1 S2 S3 S4
r (OA)
8
6
4
2
0
OA
(g
m-3
)
4321S1 S2 S3 S4
Mean (OA)
6
4
2
0
SO
42- (g
m-3
)
4321S1 S2 S3 S4
Mean (SO42-
)
Obs M1 M2 M3 M4
10
8
6
4
2
0
NO
3- (g
m-3
)
4321S1 S2 S3 S4
Mean (NO3-)
1. Introduction
Fossil-SOA: Underestimation by a factor of 6-8
Model evaluation of fossil- and biogenic SOA (Morino et al., ES&T, 2010)(CMAQ–MADRID was used.)
Biogenic-SOA: Underestimation by a factor of 1.5 - 2
Page 4
#Gas # Reaction
Aerosolmodels
MCM v3.2 5731 16933 Pankow
CACM-MADRID2
366 366 MADRID2
SAPRC99-AERO4
79 214 AERO4
SAPRC99-AERO5
88 224 AERO5
SAPRC99-VBS
92 214#1 VBS
#1: exclude aging reactions
MCM, CACM-MADRID: Explicitly simulate multi-generation oxidation
AERO4, AERO5: Yield modelsVolatility Basis Set (VBS): Grouping of
SVOC and IVOC based on volatility
from CMAQ-MADRID
CMAQ v4.6
CMAQ v4.7.1
Intercomparison of SOA models in TMA (in summer 2004)
(Morino et al., JGR, in revisions)
1.2
1.0
0.8
0.6
0.4
0.2
0.0
P(S
OA
) (g
m-3/h
r)
20151050
R(VOC+OH) (ppbv/hr)
6
5
4
3
2
1
0
P(S
OA
) (
g m
-3/h
r)
(d)
1.2
1.0
0.8
0.6
0.4
0.2
0.0
P(S
OA
) (g
m-3/h
r)
403020100P(Ox) (ppbv/hr)
6
5
4
3
2
1
0
P(S
OA
) (
g m
-3/h
r)
(c)
40
30
20
10
0
P(O
x) (
pp
bv/h
r)
20151050
R(VOC+OH) (ppbv/hr)
(c)
25
20
15
10
5
0
SO
A (g
m-3
)
12080400Ox (ppbv)
5
4
3
2
1
0
SO
A (
g m
-3)
Obs AERO4 CACM VBS AERO5 MCM
(a)
ObsS=0.193 mgm-3/ppbv
VBSS=0.130
CACMS=0.016
OthersS=0.003-0.011
1. Introduction
Page 5
Background of PM2.5 modelling in Japan SOA models:
– OA concentrations were largely underestimated by yield and mechanical models in TMA, Japan.
– VBS model better reproduced SOA in TMA.
Limitation of observational data:– Simultaneous measurement of PM2.5 chemical composition were limited in Japan.
→ Model evaluation of PM2.5 species were spatially and temporally limited.
– Simultaneous measurements of PM2.5 species over Japan were conducted in
2012.
1. Introduction
Objectives of this study
Model performance of PM2.5 chemical composition were
evaluated using the observational data over Japan in 2012. Results of three simulation models, including the VBS model,
were compared.
Page 6
Global-scale CTMMIROC-ESM-CHEM
Δx = 300 km
Regional-scale CTMWRF/CMAQ
Δx = 60km Δx = 15km
Chemical transport models
Models ChemicalModules
Aerosolmodules
① CMAQ v4.7.1 SAPRC99 AERO5② CMAQ v5.0.2 CB05 AERO6③ CMAQ v5.0.2 CB05 AERO6VBS
Target Emission data Spatial resol.
Anthropogenic (Japan)
JATOP ~1km (vehicles) ~10km (others)
Anthropogenic (Easi Asia)
REAS v2.1 0.25°
Biomass burning GFED v3.1 0.5°
Volcano AEROCOM/JMA Points
Biogenic VOC MEGAN v2.10 ~0.04°
Three versions of CMAQ
Setups of emission data
2. Methodology
Page 7
SOA models ー yield modelsAERO5
AERO6
PNCOM
POC
aging
AERO6
Carlton et al., 2010
2. Methodology
Page 8
Merit 1 :
Merit 2 :
SOA (V)
POA
VOC
Emission sources
SVOC1cond./evapo.
oxidation
VBS model
Yield model
emis.
emis.
SOA (I/S)
agingagingSVOC1
SVOC2
SVOC3
cond./evapo. cond./
evapo.
emis.SVOC3
aging
SVOC2
aging
cond./evapo.
Merit 1
Merit 2
Simulate primary emissions and oxidation (aging) of SVOC/IVOC (semi-/intermediate- VOC)
Simulate aging processes of oxidation products from VOCs
2. Methodology
SOA models ー Volatility basis-set (VBS) model
Page 9
45
40
35
30
145140135130
2
467
9
10
12
1
35
8
11
13Remote Urban/
ruralKyusyu #1:Tsushima #2:DazaifuChugoku #3:Oki #4:Matsue
Kinki #5:Kyotango #6: Osaka#7:Otsu
Chubu #8:Tateyama#11:Sadoseki
#9:Toyama#10:Niigata
Hokkaido #13:Rishiri #12:Sapporo
■Periods: - Winter: Jan 9 – 20 - Spring: May 6 – 12 - Summer: Jul 24 – Aug 1
■Points
Observations of PM2.5 species in 20122. Methodology
■Sampling duration: 6 h or 12 h
■Target species - Ion (SO4
2–, NO3–, NH4
+): IC - Carbon (EC and OC) : TOT (IMPROVE protocol)
Page 10
SO42–
NO3–
NH4+
EC
OA
45
40
35
30
145140135130
2
467
9
10
12
1
35
8
11
13
#6: Osaka#7: Shiga
#5: Kyotango
#6 Urban ( Osaka) #7 Urban (Shiga) #5 Rural (Kyotango)
Temporal variations of PM2.5 species (winter)3. Results
5
4
3
2
1
0
EC
(g
m-3
)
7/23 7/25 7/27 7/29 7/31 8/2
UTC (year of 2012)
Oki AERO5 AERO6 AERO6-VBS (Vd5 )Observation
Page 11
SO42– ・ Largely underestimated
both in urban and remote areas.
NO3– ・ Overestimated at all
sites.・ Better reproduced when Vd of HNO3&NH3 were enhanced (×5). (Neuman et al., 2004; Shimadera et al., 2014)
NH4+ ・ Combined trends of SO4
2– and NO3
–.
EC ・ Well reproduced at the urban site and underestimated at the rural site.
OA ・ Large underestimation・ Similar results by the all three models.
5
4
3
2
1
0
EC
(g
m-3
)
7/23 7/25 7/27 7/29 7/31 8/2
UTC (year of 2012)
Oki AERO5 AERO6 AERO6-VBS (Vd5 )Observation
3. Results Temporal variations of PM2.5 species (winter)
#6 Urban ( Osaka) #7 Urban (Shiga) #5 Rural (Kyotango)
Page 12
3. Results
SO42– ・ Generally reproduced,
though some peaks were underestimated.
NO3– ・ Low NO3
– was reproduced.
NH4+ ・ Combined trends of SO4
2– and NO3
–.
EC ・ Reproduced at the urban site and underestimated at the rural site.
OA ・ Underestimated by the yield models.・ VBS better reproduced the observation.
5
4
3
2
1
0
EC
(g
m-3
)
7/23 7/25 7/27 7/29 7/31 8/2
UTC (year of 2012)
Oki AERO5 AERO6 AERO6-VBS (Vd5 )Observation
Temporal variations of PM2.5 species (summer)
VBS Obs AERO5AERO6
#6 Urban ( Osaka) #7 Urban (Shiga) #5 Rural (Kyotango)
Page 13
3. Results
20
15
10
5
0
Mo
del
201612840
3 4612
1011 91 275
133 4
6121011 91 27513
3 4612
1011 91 27513
3 4
612
10 11 91 275
13
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
34612119127513346121191275133461211912751334612119127513
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
3 461210
119
12
75133 4
6121011
9
1275
133 461210
119
1275
133 4
612
10
11
9
1
27
513
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Mo
del
3.02.01.00.0
6
129
7
513
6
129
7
513
6
129
7
513
6
12
9
7
513
8
6
4
2
0
Mo
del
86420
Obs.
612 9 7513
612 9 75
136
12 9 7513
6
12 97
5
13
20
15
10
5
0
Mo
del
201612840
346
12 10119
1275
13346
12 1011 912
7513
346
12 1011 9
1275
1334
6
1210119
12
75
13
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
34612
1011
912 7
513
34612
1011
912 7
51334
6121011
912 7
513
346
121011 912
7513
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
346
12 1011
912
75
13 34612 1011
91275
13346
12 10119
1275
13 3 4 612 10
11
91
275
13
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Mo
del
3.02.01.00.0
6
129 7
13
6
129
7
13
6
129
7
13
6
12
9
7
13
8
6
4
2
0
Mo
del
86420
Obs.
612 9 7
13
6
129
7
136
12 9 713
6
129
7
13
20
15
10
5
0
Mo
del
201612840
387 4610119 125387 4610119 125387 4610119 12538 7 461011 9 125
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
3
8
74
6
1011 9
12
53
8
746
1011 9
12
5
3
8
74 6
1011 9
12
5
3
8
74
6
1011 9
1 2
5
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
38
7 461011 9
1 2
538
7 461011 9
1 253
87 46
1011 91 2
53
87 4 6
1011 91 2
5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Mo
del
3.02.01.00.0
38
74
6
912
538
74
6
912
538
74
6
912
538
7
4
6
91
2
5
8
6
4
2
0
Mo
del
86420
Obs.
38
746
91 253
874
691 253
874
691 253
8
746
9
1 2
5
Winter Spring20
15
10
5
0
Mod
el
201612840
387 4610119 125387 4610119 125387 4610119 12538 7 461011 9 125
T AERO5 T AERO6T AERO6VBS ( T Vd5)
SO42–
NO3–
NH4+
EC
OA
Comparison of observed and simulated PM2.5 species
45
40
35
30
145140135130
2
467
9
10
12
1
35
8
11
13
Urban/ruralRemote
VBS AERO5AERO6
Mod
el
Observed
Summer
Vd×5
Page 14
20
15
10
5
0
Mod
el
201612840
387 4610119 125387 4610119 125387 4610119 12538 7 461011 9 125
T AERO5 T AERO6T AERO6VBS ( T Vd5)
Comparison of observed and simulated PM2.5 species3. Results
20
15
10
5
0
Mo
del
201612840
3 4612
1011 91 275
133 4
6121011 91 27513
3 4612
1011 91 27513
3 4
612
10 11 91 275
13
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
34612119127513346121191275133461211912751334612119127513
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
3 461210
119
12
75133 4
6121011
9
1275
133 461210
119
1275
133 4
612
10
11
9
1
27
513
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Mo
del
3.02.01.00.0
6
129
7
513
6
129
7
513
6
129
7
513
6
12
9
7
513
8
6
4
2
0
Mo
del
86420
Obs.
612 9 7513
612 9 75
136
12 9 7513
6
12 97
5
13
20
15
10
5
0
Mo
del
201612840
346
12 10119
1275
13346
12 1011 912
7513
346
12 1011 9
1275
1334
6
1210119
12
75
13
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
34612
1011
912 7
513
34612
1011
912 7
51334
6121011
912 7
513
346
121011 912
7513
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
346
12 1011
912
75
13 34612 1011
91275
13346
12 10119
1275
13 3 4 612 10
11
91
275
13
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Mo
del
3.02.01.00.0
6
129 7
13
6
129
7
13
6
129
7
13
6
12
9
7
13
8
6
4
2
0
Mo
del
86420
Obs.
612 9 7
13
6
129
7
136
12 9 713
6
129
7
13
20
15
10
5
0
Mo
del
201612840
387 4610119 125387 4610119 125387 4610119 12538 7 461011 9 125
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
3
8
74
6
1011 9
12
53
8
746
1011 9
12
5
3
8
74 6
1011 9
12
5
3
8
74
6
1011 9
1 2
5
7
6
5
4
3
2
1
0
Mo
del
5.02.50.0
38
7 461011 9
1 2
538
7 461011 9
1 253
87 46
1011 91 2
53
87 4 6
1011 91 2
5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Mo
del
3.02.01.00.0
38
74
6
912
538
74
6
912
538
74
6
912
538
7
4
6
91
2
5
8
6
4
2
0
Mo
del
86420
Obs.
38
746
91 253
874
691 253
874
691 253
8
746
9
1 2
5
Winter Spring Summer
SO42– ・ Underestimated in winter
and spring.・ Well reproduced in summer.
NO3– ・ Overestimated in winter and
spring.・ Better reproduced when we enhance Vd (×5) of HNO3&NH3.
NH4+ ・ Combined characteristics of
SO42– and NO3
–.
EC ・ Well reproduced (with some variability).
OA ・ Underestimated over the three seasons・ Better reproduced by the VBS.
Mod
el
Observed
VBS AERO5AERO6
Page 15
CMAQ v4.7.1SAPRC99-AERO5
CMAQ v5.0.2CB05-AERO6
In spring and summer, AERO6VBS simulated the highest OA over Japan.
Simulated spatial distributions of organic aerosol3. Results
OA (μg m
-3)O
A (μg m-3)
OA (μg m
-3)
Spring (May)Winter (Jan.) Summer (Jul.)
CMAQ v5.0.2CB05-AERO6VBS
Page 16
In spring and summer, AERO6VBS simulated the highest OA over Japan.
Simulated spatial distributions of organic aerosol3. Results
AERO6VBS–AERO5AERO6VBS
AERO6VBS–AERO6AERO6VBS
Winter (Jan.) Spring (May) Summer (Jul.)
RatioO
A (μg m-3)
CMAQ v5.0.2CB05-AERO6VBS
Page 17
High OA concentrations by the AERO6VBS model are due to
high ASOA concentrations.
Simulated average OA over Japan3. Results
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
AERO
5
AERO
6
AERO
6VBS
AERO
5
AERO
6
AERO
6VBS
AERO
5
AERO
6
AERO
6VBS
Jan. May Jul
BSOA
ASOA
POA
OA
conc
entr
ation
s (μ
g m–3
)
Winter (Jan.) Spring (May) Summer (Jul.)
Page 18
Summary Performance of three simulation models on PM2.5 species were
evaluated over Japan in 2012.
Concentrations of SO42– , NO3
–, and NH4+ were well reproduced by
the all models in summer, while SO42– was underestimated NO3
–
was overestimated in winter and spring. OA concentrations were underestimated by all the models in
winter and spring. OA concentrations were largely underestimated by AERO5 and
AERO6 summer, and better reproduced by AERO6-VBS because higher ASOA was simulated by AERO6-VBS.
Page 20
AERO6VBS TsimpidiAnthro. BB Anthro.
Nonvolatile 0.4 0.27C*=10^(-2) 0.03C*=10^(-1) 0.06C*=10^(0) 0.26 0.27 0.09C*=10^(1) 0.40 0.42 0.14C*=10^(2) 0.51 0.54 0.18C*=10^(3) 1.43 1.50 0.30C*=10^(4) 0.40C*=10^(5) 0.50C*=10^(6) 0.80
AERO6VBS Tsimpidik(AVOC +OH) 2×10^(-11) 1×10^(-11)k(BVOC +OH) 0 0k(S/IVOC +OH) 4×10^(-11) 4×10^(-11)
Uncertainty analysis of VBS SOA yields SVOC emission profiles
SVOC aging reaction rates (cm3/molec/sec)
0.01
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000M0 (g m
-3)
ALK5, high-NOx
0.01
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000M0 (g m
-3)
ALK5, low-NOx
0.01
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000M0 (g m
-3)
ARO1, high-NOx
0.01
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000M0 (g m
-3)
ARO1, low-NOx
0.01
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000M0 (g m
-3)
ARO2, high-NOx
0.01
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000M0 (g m
-3)
ARO2, low-NOx
0.01
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000M0 (g m
-3)
TERP, high-NOx
0.01
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000M0 (g m
-3)
TERP, low-NOx
Lane, EST, 2008 Lane, AE, 2008 Tsimpidi, 2010 AERO4 AERO5 AERO6VBS
Page 21
Uncertainty analysis of VBS
Simulation [SOA]/[Ox] [V-SOA]/[Ox] [SI-SOA]/ [Ox] POA (μg m-3/ppmv) (μg m-3/ppmv) (μg m-3/ppmv) (μg m-3)
Standard 151.3 93.7 57.6 0.27 No aging 1.3 1.3 – 0.19 Aging of BVOC 152.6 95.0 57.6 0.27 Aging rate × 10 503.4 343.9 159.5 0.29 Aging rate ÷ 10 6.4 4.3 2.1 0.20 SVOC of Shrivastava et al. [2011] 290.4 117.7 172.8 1.45 SVOC of Tsimpidi et al. [2010] (low volatility case) 115.8 86.0 29.7 0.60 SVOC of Tsimpidi et al. [2010] (high volatility case) 188.3 101.0 87.3 0.28 Nonvolatile POA 89.1 89.1 – 2.36Nonvolatile POA/no aging 15.5 15.5 – 2.36AERO6VBS 178.0 94.6 83.4Obs 192.6 2.36