intercomparison of secondary organic aerosol models based on soa/o x ratio yu morino, kiyoshi...
TRANSCRIPT
Intercomparison of secondary organic aerosol
models based on SOA/Ox ratio
Yu Morino, Kiyoshi Tanabe, Kei Sato, and Toshimasa Ohara National Institute for Environmental Studies, Japan
The 12th Annual CMAS Conference, October 29, 2013
ー Contents ー １． Introduction － SOA modelling in Tokyo
２． Methodology － Box model settings
３． Results － Model evaluation / Source
contributions
４． Summary ー Acknowledgement ーFunds ： Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (23710024) Environment Research and Technology Development Fund (C-1001)
Obs. data ： Prof. Y. Kondo and Prof. N. Takegawa (Univ. Tokyo)
Urban (N=12)Rural (N=5)Roadside (N=16)
PM2.5 in Japan (2001-2010, annual average)
Ministry of Environment [2012]
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
１． Introduction
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35超過率%
70超過局日
平均濃度
有効局日数
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35超過率%
70超過局日
平均濃度
有効局日数
①Average PM2.5 was higher than 15 μgm-3 in western Japan
Western Japan
Eastern Japan(including Tokyo Metropolitan Area)
% daily PM2.5
> 35 μgm-3
# daily PM2.5
> 70 μgm-3
Monthly average PM2.5 (μgm-3)
# Stations×day
2010 2011 2012 2013
１． IntroductionPM2.5 in Japan (2010-2013, monthly average)
Ministry of Environment [2013]
②Daily PM2.5 exceeds environmental standard in all the seasons.
②Sp
ring
④Au
tum
n
①W
inte
r
②Sp
ring
④Au
tum
n
②Sp
ring
②Sp
ring
②Sp
ring
③Su
mm
er
①W
inte
r
K
SOA modelling in Tokyo Metropolican Area (Case study 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
１． Introduction
Org
anic
aer
osol
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
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
SOA model development – Volatility basis-set (VBS) model １． Introduction
ARO1 + OH = 0.224*HO2 + 0.765*RO2_R + 0.011*RO2_N + 0.055*PROD2 +0.118*GLY + 0.119*MGLY + 0.017*PHEN + 0.207*CRES + 0.059*BALD + 0.491*DCB1 + 0.108*DCB2 + 0.051*DCB3+0.071*TOLAER1 + 0.138*TOLAER2
Yield model(SAPRC99-AERO4)
UR24UR25UR26etc.
CACM (caltech chemical mechanism)
MCM (master chemical mechanism)
Near-explicit model –Explicitly simulate multi-generation reactions
SOA model development – Chemical modules １． Introduction
• Intercomparison of five SOA models (of different frameworks) to evaluate their characteristics and performance
• Preliminary evaluation of volatility basis-set (VBS) model on OA simulation in Tokyo Metropolitan Area
Characteristics of this study• Intercomparison
of SOA models A few previous studies of SOA model intercomparison
(particularly including both MCM and VBS models)
• Box model simulation
Many sensitivity simulations can be made (advantage for MCM calculations)
• Evaluation using
SOA/O ｘ ratio
Model evaluation less affected by uncertainties of meteorological fields
• Comparison for Tokyo data
OA was accurately measured by AMS/sunset-TOT Good correlation between O ｘ and SOA Behaviors of VOC and O3 are well understood
Objectives １． Introduction
SOA models
# Gas # reaction # SVOC # primary VOCs Aerosol model References
MCM v3.2 5731 16933 1902#2 105 , Pankow Jenkin et al., 2003;Saunders et al., 2003
CACM-MADRID2 366 366 43 17 , MADRID2 Griffin et al., 2002; Pun et al., 2002
SAPRC99-AERO4 79 214 10 24 , AERO4 Binkowski and Roselle, 2003
SAPRC99-AERO5 88 224 12 24 , AERO5 Carlton et al., 2010
SAPRC99-VBS 92 214#3 9 33 , VBS Tsimpidi et al., 2010
#1: estimate of this study 、 #2: C* ≤ 100 mgm3 、 #3: exclude aging reactions
Five SOA models simulated in this study
MCM, CACM-MADRID: explicitly simulate multi-generation oxidation.
- Vapor pressures used in the MCM model was calculated by EPI-Suite (Stein and Brown method). Kp was multiplied by a actor of 500 (Johnson et al., 2006).
AERO4, AERO5: Yield model
VBS: Grouping of SVOC and IVOC based on volatility (~vapor pressure).- Speciation of emitted SVOC/IVOC and aging reaction rates was the same with Tsimpidi et al. (2010).
from CMAQ-MADRID
CMAQ v4.6 CMAQ v4.7.1
2. Methodology
Processes One box model (domain: 30 x 30 km2, Fig.) including chemical, aerosol, emission, and air mass exchange.
Target period July 22 – August 12, 2004
Other conditions
Meteo. param. (T, RH, WS, BLH): observational dataBackground: 20 ppbv for O3, NMHC is from Morino et al. (2011)
Box model framework
37
36
35
Latit
ude
(°N
)
141140139138
Longitude (°E)
10
8
6
4
2
0
NO
x em
ission
(mo
le g
rid-1)
𝑑𝑋𝑑𝑡
= 𝑑𝑋𝑑𝑡 |
h𝑐 𝑒𝑚
+ 𝑑𝑋𝑑𝑡 |
𝑎𝑒𝑟𝑜
+𝐸𝑚𝑖𝑠−𝑘𝑒𝑥𝑐 (𝑋−𝑋𝑏𝑔 )
Domain
Emissions EAGrid2000 (Kannari et al., 2007)
Speciation of VOC
Vehicles ： JATOP (2012)
Evaporative ： Ministry of Env. (2003)# VOC emission data are firstly classified for MCM. Then, SAPRC/CACM data are prepared.
Observetion Period: July 24 – Aug 14, 2004Site: RCAST, Tokyo Univ# OA and OOA were measured by AMS (Takegawa et al., 2006).
2. Methodology
Obs. site
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000
M0 (g m-3
)
Obs Ng et al. Odum et al.Model AERO5 VBS AERO4(VBS: ver1 ver2)
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000
M0 (g m-3
)
Comparison of experimental data and model simulation—high NOx condition
m-xylene toluene
Obs.
VBS
AERO5
AERO4
Yi: SOA production yield Kom,i ： Partitioning coefficient
M0: OA concentration ai: stoichiometric coefficient
○Standard×No aging
Model simulation of chamber experiment (aromatics VOC + NOx + HONO) Aging process enhanced SOA production yield was enhanced by a factor of 1.3 ~ 1.5.
3. Results
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000
M0 (g m-3
)
Obs Ng et al. Odum et al.Model AERO5 VBS AERO4(VBS: ver1 ver2 ver3)
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000
M0 (g m-3
)
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000
M0 (g m-3
)
0.1
1
10
100
Yi (
%)
0.1 1 10 100 1000
M0 (g m-3
)
m-xylene toluene
Obs.
VBS
AERO5
AERO4
○Standard×No aging■reduced Yi
Model simulation of chamber experiment (aromatics VOC + NOx + HONO) Aging process enhanced SOA production yield was enhanced by a factor of 1.3 ~ 1.5.→ Yi should be reduced by 30-50% to avoid double counting.
Yi: SOA production yield Kom,i ： Partitioning coefficient
M0: OA concentration ai: stoichiometric coefficient
3. Results
Comparison of experimental data and model simulation—high NOx condition
80
60
40
20
0
O3
(pp
bv)
20151050
Time of day (JST)
Obs AERO4 AERO5 CACM VBS MCM
10x106
8
6
4
2
0
OH
(m
ole
c. c
m-3
)
20151050
Time of day (JST)
300x106
250
200
150
100
50
0
HO
2 (m
ole
c. c
m-3
)
20151050
Time of day (JST)
20
15
10
5
0
NO
(p
pb
v)
20151050
Time of day (JST)
40
30
20
10
0
NO
2 (p
pb
v)
20151050
Time of day (JST)
12
8
4
0
HN
O3
(p
pb
v)
20151050
Time of day (JST)
O3 and NOx were well reproduced.
OH were reproduced, while HO2 were underestimated.
→ should be examined in future studies. HNO3 were overestimated. (dry deposition)
Model evaluation in ambient condition – gaseous species
3. Results
OH HO2
NO2 HNO3
80
60
40
20
0
O3
(pp
bv)
20151050
Time of day (JST)
Obs AERO4 AERO5 CACM VBS MCM
10x106
8
6
4
2
0
OH
(m
ole
c. c
m-3
)20151050
Time of day (JST)
300x106
250
200
150
100
50
0
HO
2 (m
ole
c. c
m-3
)
20151050
Time of day (JST)
20
15
10
5
0
NO
(p
pb
v)
20151050
Time of day (JST)
40
30
20
10
0
NO
2 (p
pb
v)
20151050
Time of day (JST)
12
8
4
0
HN
O3
(p
pb
v)
20151050
Time of day (JST)
O3
NO
• Under VOC limited condition (e.g., urban area), VOCs+OH reactions are rate-limiting for
Ox(=O3+NO2) and SOA production.
• Ox production rate:
• SOA production rate ：
• Ratio of SOA and Ox production rate
Ki : VOC+OH reaction rateΑi : # of HO2,RO2 generated from VOC+OH reactionFi : Fraction of RO2 which produce NO2
Yi : SOA production yield
20
15
10
5
0
SO
A (g
m-3
)
12080400Ox (ppbv)
Obs AERO4 CACM VBS AERO5 MCM
Obs.S=0.155 mgm-3/ppbv
VBSS=0.108
CACMS=0.046
AERO5AERO4MCMS=0.004
20
15
10
5
0
SO
A (g
m-3
)
12080400Ox (ppbv)
VBS —StandardS=0.108
VBS —Reduced yieldS=0.084
VBS —No agingS=0.005
AERO5 S=0.016AERO4 S=0.010
Obs.S=0.155 mgm-3/ppbv
=SOA formation potential of VOCOx formation potential of VOC
Model evaluation using SOA/Ox ratio3. Results
1.0
0.8
0.6
0.4
0.2
0.0
SO
A /
(SO
A +
SV
OC
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
VBS CACM AERO5 MCM (std. Kp) MCM (Kp x 500)
10-6
10-4
10-2
100
102
SV
OC
(g
m-3
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
10-6
10-4
10-2
100
102
SO
A +
SV
OC
(g
m-3
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
10-6
10-4
10-2
100
102
SO
A (g
m-3
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
VBS CACM AERO5 MCM (std. Kp) MCM (Kp x 500)
1.0
0.8
0.6
0.4
0.2
0.0
SO
A /
(SO
A +
SV
OC
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
VBS CACM AERO5 MCM (std. Kp) MCM (Kp x 500)
10-6
10-4
10-2
100
102
SV
OC
(g
m-3
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
10-6
10-4
10-2
100
102
SO
A +
SV
OC
(g
m-3
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
10-6
10-4
10-2
100
102
SO
A (g
m-3
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
VBS CACM AERO5 MCM (std. Kp) MCM (Kp x 500)
Intercomparison of volatility (C*) distributions3. Results
Saturation concentration Saturation concentration
SOA(aerosol)
SVOC(gas)
SOA+SVOC(total)
SOASOA+SVOC
Continuous C* distributions in VBS and MCM.MCM simulated very small [SOA+SVOC] with C*<10 μgm-3.
1.0
0.8
0.6
0.4
0.2
0.0
SO
A /
(SO
A +
SV
OC
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
VBS CACM AERO5 MCM (std. Kp) MCM (Kp x 500)
10-6
10-4
10-2
100
102
SV
OC
(g
m-3
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
10-6
10-4
10-2
100
102
SO
A +
SV
OC
(g
m-3
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
10-6
10-4
10-2
100
102
SO
A (g
m-3
)
10-2
10-1
100
101
102
103
104
105
C* (g m-3
)
VBS CACM AERO5 MCM (std. Kp) MCM (Kp x 500)
(aerosol/total)
Contributions of precursors/sources to Ox and SOAContributions of precursor VOCs were estimate from sensitivity simulations (20% recuction of each VOC).
40
30
20
10
0
Ox
(pp
bv)
MC
M
CA
CM
AE
RO
4
AE
RO
5
VB
S
3
2
1
0
SO
A (g
m-3
)
MC
M
CA
CM
AE
RO
4
AE
RO
5
VB
S
ALK ARO BIO OLE others S/IVOC
OLE
SVOC
ARO
Contributions of each precursor VOC
ARO
OLE
others
ALK
40
30
20
10
0
Ox
(pp
bv)
MC
M
CA
CM
AE
RO
4
AE
RO
5
VB
S
3
2
1
0S
OA
(g
m-3
)
MC
M
CA
CM
AE
RO
4
AE
RO
5
VB
S
#1 #2 #3 #4 #5 #6 #7 #8 #9 #10
Contributions of emission sources
Vehicles
Paint
Fugitive Paint
Vehicles
3. Results
Summary
• Five organic aerosol models (MCM, CACM SAPRC99-AERO4,
SAPRC99-AERO5, SAPRC99-VBS) were compared using a box
model.
• Aging reactions enhanced SOA production yield by a factor of 1.3 ~
1.5 under conditions of chamber experiments. SOA production
yield should be reduced by 30-50% to avoid double counting.
• SOA/Ox ratio was well reproduced by the VBS model, while other
models significantly underestimated the observed ratio.
• Source contributions to ambient SOA concentration largely differed
among the five models. Choice of SOA model is critical in the
source apportionment of SOA.
4. Summay
1.0
0.8
0.6
0.4
0.2
0.0
C3
H6
(p
pb
v)
2015105
0.5
0.4
0.3
0.2
0.1
0.0
X1
_C
4H
8 (
pp
bv)
2015105
0.5
0.4
0.3
0.2
0.1
0.0
cis_
2_
C4
H8
(p
pb
v)
2015105
5
4
3
2
1
0
AR
O1
(p
pb
v)
2015105
20
15
10
5
0
AL
KL
(p
pb
v)
2015105
3.0
2.5
2.0
1.5
1.0
0.5
0.0
OL
E1
(p
pb
v)
2015105
3.0
2.5
2.0
1.5
1.0
0.5
0.0
C2
H4
(p
pb
v)
2015105
1.0
0.8
0.6
0.4
0.2
0.0
C5
H8
(p
pb
v)
2015105
0.5
0.4
0.3
0.2
0.1
0.0
BE
NZ
EN
E (
pp
bv)
2015105
4
3
2
1
0
TO
LU
EN
E (
pp
bv)
2015105
3.0
2.5
2.0
1.5
1.0
0.5
0.0
C2
H6
(p
pb
v)
2015105
4
3
2
1
0
C3
H8
(p
pb
v)
2015105
1.2
0.8
0.4
0.0
C2
H2
(p
pb
v)
2015105
3.0
2.5
2.0
1.5
1.0
0.5
0.0
i_C
4H
10
(p
pb
v)
2015105
4
3
2
1
0
n_
C4
H1
0 (
pp
bv)
2015105
4
3
2
1
0
i_C
5H
12
(p
pb
v)
2015105
2.0
1.5
1.0
0.5
0.0
n_
C5
H1
2 (
pp
bv)
2015105
1.0
0.8
0.6
0.4
0.2
0.0
n_
C6
H1
4 (
pp
bv)
2015105
2.0E-2
2.0E-1
2.0E+0
Obs MCM
モデルー観測データの比較 (VOC 成分 )
３．結果 －ボックスモデル計算結果、寄与解析
上記の比較を基に、 VOC の排出量を補正。右図は補正後の VOC濃度。測定成分 (C5H8 を除いた 14 成
分 ) のみ補正した点に注意 MCM, CACM, SAPRC99 で芳香族
濃度が異なるのは、グルーピングが異なり、 OH との反応速度も異なるため
NMHC 濃度の観測値とモデル計算結果( 期間平均濃度、 ppbv)
80
60
40
20
0
O3
(pp
bv)
20151050
Time of day (JST)
Obs AERO4 AERO5 CACM VBS MCM
10x106
8
6
4
2
0
OH
(m
ole
c. c
m-3
)
20151050
Time of day (JST)
300x106
250
200
150
100
50
0
HO
2 (m
ole
c. c
m-3
)
20151050
Time of day (JST)
20
15
10
5
0
NO
(p
pb
v)
20151050
Time of day (JST)
40
30
20
10
0
NO
2 (p
pb
v)
20151050
Time of day (JST)
12
8
4
0
HN
O3
(p
pb
v)
20151050
Time of day (JST)
VOC 成分の日変動