Sensitivity study on Ammonia Emission
Impacts on Fine Particles in China
A&WMA International Specialty Conference, Xi’an
May 12st, 2010
Jia Xinga, Shuxiao Wanga, Carey J.Jangb, Jiming Haoa
a Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084, CHINA
b Office of Air Quality Planning & Standards, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Outline
� Background
� Serious airborne particle problem in China
� Ammonia impacts on Secondary Inorganic Aerosols (SIA)
� Objective and Methodology
� Development of RSM-CMAQ model
� Validation of the model system
� Results and discussion
� Impacts of ammonia on SIA (static & dynamic sensitivity)
� Potential AQ benefit from future NH3 controls strategy
� Conclusion
0
50
100
150
1985 1990 1995 2000 2005 2010
Year
PM
2.5
co
nce
ntr
atio
n (
ug
/m3)
Chen et al., 1994
He et al., 2001
Zheng et al., 2005
Duan et al.,2006
Zhao et al.,2009
Pathak et al.,2008
0
50
100
150
1998 2000 2002 2004 2006
YearP
M2
.5 c
on
ce
ntr
atio
n (
ug
/m3)
Ye et al.,2003
Huang et al.,2009
Wang et al.,2006
Feng et al.,2009
Pathak et al.,2008
0
50
100
150
2000 2001 2002 2003 2004 2005
Year
PM
2.5
co
nce
ntr
atio
n (
ug
/m3)
Andreae et al,2008
Lai et al.,2007
Cao et al.,2003
Pathak et al.,2008
Huang et al.,2007
Serious airborne particle problem in China
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) 150 to 184 (3)
) 100 to 150 (50)
) 40 to 100 (59)
) 20 to 40 (1)
Half of Chinese cities cannot meet the CNAAQS – II of PM10 annual concentration (100 microgram per m3).
High PM2.5 concentration in megacities has been frequently reported during last decade.
Annual mean Conc. (ug/m3, 2005)
Beijing
Shanghai
Guangzhou
Part 1 Background
Compositions and sources of fine particles
� Chemical compositions (Chan C.K and Yao X.H, 2007)
� Inorganic species (22~54%)• Sulfate, Nitrate, Ammonium
� Carbonaceous species (27~42%)
• organic carbon
• and elemental carbon
� Crustal species (11~16%)
• Al, Si, Ca, Mg, Fe, etc.
� Major Sources
� Primary emissions
• fossil / bio- fuel burning, fugitive emissions from industry plants and traffic road, dust, etc.
� Secondary sources
• chemical reactions among precursors as NOx, SO2, NH3, VOC.
Part 1 Background
Secondary Inorganic Aerosols (SIA) is one dominant contributor to fine particles
Non-linear system during SIA formation
Linkage between SIA with precursors
Processes involving� Photochemistry� Multi-phase reactions� Aerosol thermodynamics � Along with precursors emissions, physical
transport, wet-dry depositions, particle formation condensation, coagulation, cloud scavenging…
Sensitivity studies on SIA
• SO2 vs NOx impactsMueller et al., ES&T, 2004; Blanchard et al., A&WMA, 2007
• SO2 vs NH3 impactsTsimpidi et al., A&WMA, 2007
• NOx vs VOC impactsTsimpidi et al., A&WMA, 2008
• NH3 impactsRedington et al., AE, 2009
• SO2, NOx vs NH3 impactsPinder et al., ES&T, 2007
• NOx, VOC vs NH3 impactsNguyen et al., AST, 2002
• SO2, NOx, NH3, VOC, CO impactsDerwent et al., AE, 2009
1. Considerable ammonia impacts
2. Highly non-linear system brings
heavy computational requirements
Part 1 Background
Anthropogenic ammonia emissions in China
poult
16%
otani
5%
urea
26%
abc
15%
cows
1%cattle
6%
pig
15%
others fertillizer
9%
Industry
1%
waste
5% Other
1%
Livestock
43%
Source contribution
Emission intensity
(t·km-2)
Livestock and fertilizer application are the major sources (~90%).
Heavy ammonia emissions condensed in Mid-East China.
Strong seasonal variation, higher from May to July.
Part 1 Background
Dong W.X, Xing J. and Wang S.X, (2010).
Seasonal variation (Streets D. G., et al, 2003)
Spatial distribution
Historical trend of major precursors’ emissions
0
5
10
15
20
1950
1960
1970
1980
1990
2000
2010 Year
NH
3 E
mis
ssio
n /
Tg. Wang et al.,1997
Sun et al.,1997
Klimont,2001
Streets,2003
Wang et al.,2009
Tsinghua
Along with the growth of SO2,
NOx and VOC emissions, NH3
emissions are continually increasing. (doubled in 2005 compared to 1980)
Part 1 Background
0
10
20
30
40
1980 1985 1990 1995 2000 2005 2010
Year
SO
2 E
mis
sio
ns
(Tg
)
Kato et al. 1992; Akimoto et al., 1994
Fujita et al., 1991
Bai et al.,1996
Wang et al., 1996
Shrestha et al., 1996
Shah et al., 2000 (Rains-Asia)
Streets et al., 2000
Vallack et al., 2001
Woo et al., 2003
Yang et al.,2004
EDGAR V.2.0
EDGAR V.3.2
Streets et al., 2001
Klimont et al., 2001
Streets et al., 2003
China EPB
Xue et al., 1998
INDEX-B
Tsinghua
0
5
10
15
20
25
1980 1985 1990 1995 2000 2005 2010
Year
NO
x E
mis
sio
ns
(Tg
)
Kato et al. 1992; Akimoto et al., 1994
Fujita et al., 1991
Bai et al., 1996
Wang et al., 1996
Aardenne et al., 1999
Tian et al., 2002; Hao et al., 2002
Sun et al., 2004
Vallack et al., 2001
Woo et al., 2003
EDGAR V.2.0
EDGAR V.3.2
Streets et al., 2001
Klimont et al., 2001
Streets et al., 2003
Xue et al., 1998
INDEX-B
China EPB
Tsinghua
0
5
10
15
20
25
1980 1985 1990 1995 2000 2005 2010
Year
VO
C E
mis
sio
ns
(Tg
)EDGAR V.2.0
EDGAR V.3.2
Klimont et al., 2001
Streets et al., 2003
Piccot et al., 1992
Tonooka et al., 2001
Klimont et al., 2002
INDEX-B
Tsinghua
SO2
VOC
NOx
NH3
National emissions growth trend in China
Framework of this studyPart 2 Methodology
Objective: evaluate the ammonia impacts in a highly non-linear complex model system
Air Quality modeling
Response surface model experimental design
Training samples
RSM predicted system
Sensitivity study on SIA responses
ValidationPredictor
Evaluation
Gridded emissions in 2005
(Base year)
Historical emission trend
starts from 1980s
Future emission
projections up to 2030
Multi-Emission scenarios
0
0.2
0.4
0.6
0.8
1
00.2
0.40.6
0.810
0.2
0.4
0.6
0.8
1
Multi-case Impacts
MM5v3 / CMAQ4.7
Target period: July 1st ~31st 2005
0
0.5
1
1.5
2
0
0.5
1
1.5
2
0
0.5
1
1.5
2
NOx control factorSO2 control factor
NH
3 c
ontr
ol fa
cto
r
0
2.000
4.000
6.000
8.000
10.00
12.00
14.00
16.00
Source A Source B
Sourc
e C
Pollutant
Validation of Base year simulation (year 2005)
0.1 1 10 100
0.1
1
10
100
OMI NO2 VCD
All grid
NCP
PRD
YRD
CM
AQ
12
km
NO
2 V
CD
y=0.25xy=x
y=2x
y=4x
y=0.5x
0.01 0.1 1 10
0.01
0.1
1
10
SCIAMACHY SO2 VCD
All grid
NCP
PRD
YRD
CM
AQ
36km
SO
2 V
OC
y=0.25xy=x
y=2x
y=4x
y=0.5x
0.01 0.1 1 10
0.01
0.1
1
10
MODIS AOD
All grid
NCP
PRD
YRD
CM
AQ
36km
AO
D
y=0.25xy=x
y=2x
y=4x
y=0.5x
NO2 TroposphericColumn density
SO2 TroposphericColumn density
Aerosol optical depth
Satellite CMAQ
OMI 0.125o×0.125o
SCIMACHY: 0.5o×0.5o
MODIS/Terra: 1o×1o
Blue: North China Plain, Orange: Yangtz river delta, Green: Pearl river delta
Grid-to-gird comparison
2005 summer time
Part 2 Methodology
Validation of model performance on SIA simulation
0
100
200
300
12-3
1
1-3
1
2-2
8
3-3
1
4-3
0
5-3
1
6-3
0
7-3
1
8-3
1
9-3
0
10-3
1
11-3
0
Con
centr
ation
(ug
/m3) Obs
Sim
0
100
200
300
12-3
1
1-3
1
2-2
8
3-3
1
4-3
0
5-3
1
6-3
0
7-3
1
8-3
1
9-3
0
10-3
1
11-3
0
12-3
1
Co
ncentra
tio
n (ug
/m3) Obs
Sim
0
10
20
30
12-3
1
1-3
1
2-2
8
3-3
1
4-3
0
5-3
1
6-3
0
7-3
1
8-3
1
9-3
0
10-3
1
11-3
0
Con
centr
ation
(ug
/m3) Obs
Sim
0
10
20
30
12-3
1
1-3
1
2-2
8
3-3
1
4-3
0
5-3
1
6-3
0
7-3
1
8-3
1
9-3
0
10-3
1
11-3
0
12-3
1
Co
ncentra
tio
n (ug
/m3) Obs
Sim
0
10
20
30
40
50
60
12-3
1
1-3
1
2-2
8
3-3
1
4-3
0
5-3
1
6-3
0
7-3
1
8-3
1
9-3
0
10-3
1
11-3
0
Con
centr
ation
(ug
/m3) Obs
Sim
0
10
20
30
40
50
60
12-3
1
1-3
1
2-2
8
3-3
1
4-3
0
5-3
1
6-3
0
7-3
1
8-3
1
9-3
0
10-3
1
11-3
0
12-3
1
Co
ncentra
tio
n (ug
/m3) Obs
Sim
0
10
20
12-3
1
1-3
1
2-2
8
3-3
1
4-3
0
5-3
1
6-3
0
7-3
1
8-3
1
9-3
0
10-3
1
11-3
0
Con
centr
ation
(ug
/m3) Obs
Sim
0
10
20
12-3
1
1-3
1
2-2
8
3-3
1
4-3
0
5-3
1
6-3
0
7-3
1
8-3
1
9-3
0
10-3
1
11-3
0
12-3
1
Co
ncentra
tio
n (ug
/m3) Obs
Sim
PM2.5
NO3-
SO42-
NH4+
Beijing Urbanweekly mean.
Part 2 Methodology
Beijing Rural
Validation of RSM-Predicted system
Validation Methods:
�Cross validation R > 0.99
�Out of sample validation NME <10%
�Isopleths validation R > 0.99
Sulfate NOx vs SO2 NOx vs NH3 SO2 vs NH3
R1
R2
Nitrate NOx vs SO2 NOx vs NH3 SO2 vs NH3
R1
R2
-0.54
0.84
2.2
3.6
5.0
6.4
7.8
9.1
11
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
SO
2
NH3
1.7
3.9
6.1 8.311
13
15
17
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
NH
3
NOX
1.3
3.0
4.6
6.3
8.09.7
11
13
15
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
SO
2
NOX
-0.59
0.772.1
3.5 4.9 6.2
7.6
8.9
10
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
SO
2
NH3
-0.14
2.0
4.2
6.3 8.5
1113
15
17
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
NH
3
NOX
0.90
2.6
4.36.0
7.7
9.4
11
13
14
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
SO
2
NOX
3.0
5.3
7.6
9.9
12
14
17
1921
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
SO
2
NH3
8.7
9.1
9.6
10 10
11 11
12
12
10
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
NH
3
NOx
2.6
4.8
6.9
9.0
11
13
15
18
20
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
SO
2
NOX
2.7
5.0
7.3
9.6
12
14
17
19
21
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
SO
2
NH3
9.2
9.610.0
10
11
11
12 12
12
10
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
NH
3
NOX
2.8
4.9
7.0
9.1
11
13
15
18
20
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
SO
2
NOX
Isopleths comparison (Beijing site)
R1: Two variables RSM (30); R2: Five variables RSM(100)
Part 2 Methodology
NME PM2. 5 Sul f at e Ni t r at eBei j i ng 1% 4% 2%Mi yun 1% 2% 2%Ti anj i n 1% 5% 3%Shanghai 3% 3% 4%Guangzhou 2% 1% 2%Ni ngbo 3% 2% 8%Dal i an 1% 4% 2%Nanj i ng 2% 3% 2%Ji ' nan 3% 3% 4%Shi j i azhuang 1% 5% 6%Zhengzhou 1% 2% 3%Xi ' an 1% 3% 3%Tai yuan 2% 4% 6%Shenyang 2% 2% 8%Hangzhou 2% 3% 7%
Out of sample validation (12cases)
NME for Reduction ratio of concentration
List of cases conducted in this study
� Change NH3 emissions alone
� Reduce by 50% (= 1980 level) and Increase by 30% (= 2030 level)
� Change all emission including NH3, SO2, NOx, VOC and PM
� Static sensitivity: keep the same emission level of other species
� Dynamic sensitivity: when other species emission changes
� Potential benefit from future NH3 control strategy
� Extra NH3 control effects base on current SO2/NOx control strategy
� Possible risk from acid deposition effects
Part 3 Results & discussion
Base case:
�July, 2005 (monthly mean)
Pollutants: � PM2.5, Sulfate, Nitrate
Target Sites:
� 18 cities
PM2.5 reduced by 4~20%
Sulfate reduced by 4~20%
Nitrate reduced by 20~80%
NH3 reduced by 50%
NH3 increased by 30%
PM2.5 increased by 0~8%
Sulfate increased by 0~10%
Nitrate increased by 0~50%
Ammonia reduction is benefit for the particle control
Nitrate is more sensitive to ammonia emissions
SO42-PM2.5 NO3
-
Static sensitivity analysis
——NH3 impacts
0%
100%
0.9 0.7 0.5 0.3 0.1
Emission ratio
Co
ntr
ibu
tio
n
PM
VOC
NH3
SO2
NOx
-10%
30%
70%
110%
0.9 0.7 0.5 0.3 0.1
Emission ratio
Re
lative
Co
ntr
ibu
tio
n
PM
VOC
NH3
SO2
NOx
-10%
100%
0.9 0.7 0.5 0.3 0.1
Emission ratio
Co
ntr
ibu
tio
n
PM
VOC
NH3
SO2
NOx
-20%
0%
20%
40%
60%
80%
100%
0.9 0.7 0.5 0.3 0.1
Emission ratio
Re
lative
Co
ntr
ibu
tio
n
PM
VOC
NH3
SO2
NOx
0%
100%
200%
0.9 0.7 0.5 0.3 0.1
Emission ratio
Co
ntr
ibu
tio
n
PM
VOC
NH3
SO2
NOx
-10%
30%
70%
110%
0.9 0.7 0.5 0.3 0.1
Emission ratio
Re
lative
Co
ntr
ibu
tio
n
PM
VOC
NH3
SO2
NOx
SO42-
PM2.5
NO3-
-20% 0% 20% 40% 60% 80% 100%
Beijing
Tianjin
Shanghai
Guangzhou
Ningbo
Dalian
Nanjing
Ji'nan
Shijiazhuang
Zhengzhou
Xi'an
Taiy uan
Sheny ang
Hangzhou
NOx SO2 NH3 VOC PM
-20% 0% 20% 40% 60% 80% 100%
Beijing
Tianjin
Shanghai
Guangzhou
Ningbo
Dalian
Nanjing
Ji'nan
Shijiazhuang
Zhengzhou
Xi'an
Taiy uan
Sheny ang
Hangzhou
NOx SO2 NH3 VOC PM
-20% 0% 20% 40% 60% 80% 100%
Beijing
Tianjin
Shanghai
Guangzhou
Ningbo
Dalian
Nanjing
Ji'nan
Shijiazhuang
Zhengzhou
Xi'an
Taiy uan
Sheny ang
Hangzhou
NOx SO2 NH3 VOC PM
37~46%
6~21%
5~33%
The relative contribution of
NH3 to fine particle is comparable with SO2 and NOx.
Effects on NO3- become larger
under strengthened NH3
control level.
Static sensitivity analysis
—Impacts of SO2/NOx/NH3 on PM
0% 50% 100% 150%
Beijing
Tianjin
Shanghai
Guangzhou
Ningbo
Dalian
Nanjing
Ji'nan
Shijiazhuang
Zhengzhou
Xi'an
Taiy uan
Sheny ang
Hangzhou
NH3 NOx SO2 VOC
0% 50% 100% 150%
Beijing
Tianjin
Shanghai
Guangzhou
Ningbo
Dalian
Nanjing
Ji'nan
Shijiazhuang
Zhengzhou
Xi'an
Taiy uan
Sheny ang
Hangzhou
NH3 NOx SO2 VOC
Dynamic sensitivity analysis
——Historical impacts
Hypothetic emission trend from 1990-2005
The growth of ammonia
emissions enhance ~40% increase of sulfate and nitrate.
39(11~73)% 39(24~58)%
0
0.5
1
1.5
2
2.5
1990 1995 2000 2005
Year
Em
issio
n R
atio
(Y1990=
1)
SO2 NOx VOC NH3
0
1
2
3
4
1990 1995 2000 2005Year
Incr.
Ratio
base
NH3_fixed
NOx_fixedSO2_fixed
VOC_fixed
0.8
1
1.2
1.4
1.6
1990 1995 2000 2005Year
Incr.
Ratio
base
NH3_fixed
NOx_fixed
SO2_fixed
VOC_fixed
SO42-
NO3-
0
0.5
1
1.5
2
2005 2010 2015 2020 2025 2030
Year
Co
nc. R
esp
on
se
(Y2
00
5=
1)
REF0_nonNH3incr REF0_NH3incr
PC2_nonNH3incr PC2_NH3incr
Zhang C Y, Wang S X, Xing J. et al. (2008).
Emission projection from 2005-2030
0
0.5
1
1.5
2
2.5
2005 2010 2015 2020 2025 2030
Year
Em
issio
n R
atio(Y
2005=
1) REF0 PC0
PC1 PC2
0
5
10
15
20
25
2005 2010 2015 2020 2025 2030Year
Em
isssio
n a
mo
un
t(T
g)
0.8
0.9
1
1.1
1.2
1.3
Em
issio
n r
atio
(Y2
00
5=
1)
Emission Amount Emissin Ratio
0
0.5
1
1.5
2
2005 2010 2015 2020 2025 2030
Year
Em
issio
n R
atio(Y
2005=
1) REF0 PC0
PC1 PC2
SO2 NOx
0
0.5
1
1.5
2
2005 2010 2015 2020 2025 2030
Year
Co
nc. R
esp
on
se
(Y2
00
5=
1)
REF0_nonNH3incr REF0_NH3incr
PC2_nonNH3incr PC2_NH3incr
SO42-
NO3-
The future ammonia emissions will
continually enhance 4~8% increase of sulfate and nitrate.
Dynamic sensitivity analysis
——Future impacts
Future SIA concentration from 2005-2030
NH3
0%
10%
20%
30%
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1NH3 emission control ratio
Co
nc. re
du
ctio
n r
atio
Potential NH3 control benefit
——Extra benefit
0%
20%
40%
60%
80%
100%
120%
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1NH3 emission control ratio
Co
nc. re
du
ctio
n r
atio
0%
10%
20%
30%
40%
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1NH3 emission control ratio
Co
nc. re
du
ctio
n r
atio
SO42- NO3
-
Robustness of NH3 reduction benefit
Emission ratios of SO2 and NOx change between 0.5~2.0
PM2.5
0.5
Extra NH3 reduction is effective
under current / future SO2/NOx control strategy.
——potential solution when
extra PM reduction needed while SO2/NOx become hardly
controlled (with larger marginal cost).
Conclusions
� Ammonia reduction is benefit for the particle control, specially for nitrate which is more sensitive to ammonia emissions.
� The importance of NH3 emission to fine particle is
comparable with SO2 and NOx, with 6~21% relative contribution.
� The growth of ammonia emissions enhance ~40% increase of sulfate and nitrate, starting from 1990.
� The future ammonia emissions will continually
enhance 4~8% increase of sulfate and nitrate, till 2030.
� NH3 emission reduction is effective under current / future SO2/NOx control strategy.
Part 4 Conclusions
Uncertainty and Future plan
� Impacts from Seasonal variations
� Risk evaluation, such as enhancing acid deposition
Part 4 Conclusions
Potential NH3 control benefit
——Risk evaluation
1.01.5
1.9
1.9
0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
NH
3 c
on
tro
l ra
tio
NOx control ratio
1.0 1.41.8
0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
NH
3 c
on
tro
l ra
tio
SO2 control ratio
Degree of Sulfate Neutralization (DSN)
NH3 rich
NH3 rich
Base 50% NH3 reduction
The Reduction of NH3 emission
within 50% control won’t have negative effects on acid deposition.
Thank you !
And waiting for your comments !
